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The impact of advanced technologies on the workplace and the workforce: an evaluation study
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Content
Running head: THE IMPACT OF ADVANCED TECHNOLOGIES ON THE
WORKPLACE AND THE WORKFORCE: AN EVALUATION STUDY
Copyright 2019 Carly E. Cooper
1
THE IMPACT OF ADVANCED TECHNOLOGIES ON THE WORKPLACE AND THE
WORKFORCE: AN EVALUATION STUDY
Carly E. Cooper
A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION
May 2019
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WORKFORCE
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Dedication
To Thomas, may you always be curious, ask lots of questions and reach for your dreams.
To James, thank you for always being my champion, my partner, the best father to
Thomas and a best friend to me. Thank you for encouraging me, listening to me, and supporting
me. You’ve made so many of my dreams already come true.
To Mom, Dad, Betsy, Mac, Quinn and Beckett, thank you for always believing in me; I
will always try to make you proud.
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Acknowledgments
According to an African Proverb, “If you want to go fast go alone; if you want to go far,
go together.” I would not have been able to come this far without the support of so many people.
Thank you to my chair, Dr. Helena Seli for her support and encouragement throughout my time
at USC. Thank you to my committee member, Dr. Douglas Lynch who coached me, pushed me,
and supported me in my thinking and my creativity. Thank you to Dr. Roger Schank, whose
expertise on A.I. and general candor raises human intelligence.
A doctorate is a family affair. Thank you to my husband James who supported me
throughout this endeavor, ensuring that I could attend hours of class each week while my
classmates never heard a peep from our newborn son. Thank you to Thomas for making me want
to be the best person I can be.
My passion for learning was reignited by some amazing colleagues over the years. To
Sam, Sanjay, Jason and Vishal thank you for inspiring me and believing in me. Thank you to my
Columbia faculty and XMA cohort who nurtured me as a learner. To my USC cohort who
thankfully had a personality better than hummus and sparked curiosity about cheesy fries, thank
you. Finally, a thank you to a friend and learning partner who spanned both master and doctorate
degrees; Durand, may we never stop learning together.
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Table of Contents
Dedication ....................................................................................................................................... 2
Acknowledgments ........................................................................................................................... 3
List of Tables .................................................................................................................................. 8
List of Figures ................................................................................................................................. 9
Abstract ......................................................................................................................................... 10
Introduction to the Problem of Practice ........................................................................................ 11
Context of Field of Practice .......................................................................................................... 11
Importance of Addressing the Problem ........................................................................................ 12
Global Goal ................................................................................................................................... 13
Stakeholder Group of Focus and Stakeholder Goal ...................................................................... 13
Purpose of the Project and Questions ........................................................................................... 14
Methodological Approach ............................................................................................................ 15
Review of Literature ..................................................................................................................... 16
Past Industrial Revolutions ....................................................................................................... 16
The Present Industrial Revolution ............................................................................................ 17
A.I. Defined .............................................................................................................................. 19
What Artificial Intelligence Can Do ......................................................................................... 20
Adoption of A.I. Impacts Organizational Culture, Mindsets, and Skill Sets ............................ 21
Chief Learning Officer Knowledge, Motivation and Organizational Influences ......................... 22
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Knowledge Influences .............................................................................................................. 23
Motivation Influences ............................................................................................................... 25
Organizational Influences ......................................................................................................... 27
Conceptual Framework: The Interaction of Chief Learning Officers’ Knowledge, Motivation
and the Organizational Context .................................................................................................... 31
Participating Stakeholders: Sampling and Recruitment ............................................................... 33
Sampling Criteria and Rationale ............................................................................................... 34
Sampling Strategy and Rationale .............................................................................................. 34
Explanation for Choices ............................................................................................................ 35
Data Collection and Instrumentation ............................................................................................ 35
Interviews .................................................................................................................................. 36
Documents and Artifacts ........................................................................................................... 36
Data Analysis ................................................................................................................................ 37
Results and Findings ..................................................................................................................... 37
Research Questions ................................................................................................................... 38
Participating Organizations and Stakeholders .......................................................................... 38
Finding 1: CLOs Report to be Knowledgeable about the Future of Work ............................... 39
Finding 2: CLOs Report to be Motivated to Prepare their Workforce for the Future .............. 43
Finding 3: Organizational Culture and Context Impacts CLOs’ Capacity to Develop the
Workforce for the Future .......................................................................................................... 46
Finding 4: CLOs Posit that as Technology Continues to Advance, Organizations Need to
Adapt ......................................................................................................................................... 52
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Summary of Key Findings ........................................................................................................ 56
Recommendations for Practice ..................................................................................................... 57
Knowledge Recommendations ................................................................................................. 59
Motivational Recommendations ............................................................................................... 63
Organizational Recommendations ............................................................................................ 65
Integrated Implementation and Transformational Program for CLOs ......................................... 68
Implementation and Evaluation Framework ................................................................................. 68
Organizational Purpose, Need, and Expectations ..................................................................... 69
Level 4: Results and Leading Indicators ................................................................................... 69
Level 3: Behavior ...................................................................................................................... 70
Level 2: Learning ...................................................................................................................... 73
Level 1: Reaction ...................................................................................................................... 77
Evaluation Tools ....................................................................................................................... 78
Limitations and Delimitations ....................................................................................................... 80
Recommendations for Future Research ........................................................................................ 81
Conclusion .................................................................................................................................... 84
References ..................................................................................................................................... 86
Appendix A: Interview Protocol ................................................................................................... 94
Appendix B: Document Analysis Protocol ................................................................................... 98
Appendix C: Credibility and Trustworthiness .............................................................................. 99
Appendix D: Ethics ..................................................................................................................... 100
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List of Tables
Table 1. Organizational Mission, Global Goal and Stakeholder Performance…………………..14
Table 2. Chief Learning Officers Knowledge Type and Knowledge Influence…………………25
Table 3. Chief Learning Officers Motivation Type and Motivation Influence………………….27
Table 4. Organizational Influences………………………………………………………………31
Table 5. Participating Organizations and CLOs…………………………………………………39
Table 6. Summary of Knowledge, Motivational and Organizational Influences and
Recommendations………………………………………………………………………………..58
Table 7. Outcomes, Metrics, and Methods for External and Internal Outcomes………………..70
Table 8. Critical Behaviors, Metrics, Methods, and Timing for Evaluation………………….…71
Table 9. Required Drivers to Support Critical Behaviors………………………………………...72
Table 10. Evaluation of the Components of Learning for the Program………………………….76
Table 11. Components to Measure Reactions to the Program…………………………………...77
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List of Figures
Figure 1. The external environment and the impact on industry, organizational context, and
CLO’s knowledge and motivation……………………………………………………………….32
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Abstract
Technical advancement is predicted to impact the workforce and will require the
reskilling of many. This study sought to understand the preparations large enterprises are taking
to prepare their workforce and their workplace for the impact of advanced technologies.
Specifically, this paper explored the knowledge, motivation, and organizational influences that
influence the Chief Learning Officer’s (CLOs) ability to prepare their workforce for the future.
Clark and Estes’ (2008) gap analysis model influence the conceptual and methodological
framework for the study along with the Burke-Litwin (1992) model for organizational change.
Interviews were conducted with seven CLOs at large enterprises.
The research explored the CLOs’ knowledge and motivation related to creating a
leadership and development strategy to develop their workforce, considering their organizations’
adoption of advanced technologies. The data suggested CLOs are knowledgeable and motivated
about preparing their workforce for the future of work. The research also explored how
organizational culture and context supported or hindered CLO knowledge and motivation. The
data suggested that indeed organizational cultural models and organizational cultural settings
impact the CLOs’ ability to reach their goals.
Recommendations for developing a transformational adult learning program for CLOs
was proposed. The program design, metrics and critical behaviors needed to evaluate the
effectiveness of the proposed program was influenced by Kirkpatrick model by also took an
anagogical approach. The practices identified supported the continued development of
knowledge, motivation and organizational cultures to help prepare large enterprises’ workforce
and workplace for the impact of advanced technologies.
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Introduction to the Problem of Practice
The World Economic Forum Future of Jobs Report (2016) called for targeted action to
build a workforce with “futureproof skills” (p. 11) to balance the influence of technological,
demographic, and socio-economic changes. Technological advancement is predicted to impact
almost half (47%) of the total United States workforce with jobs at high-risk of automation, and
therefore elimination, in 20 years (Frey & Osborne, 2013). Moreover, the World Economic
Forum has predicted five million jobs worldwide will be automated by 2020 (WEF, 2016). The
advancement of technology represents one of the key drivers influencing the skills needed in the
future and will require the reskilling of many individuals (WEF, 2016). In fact, technology may
have advanced faster than some professional development (Brynjolfsson & McAfee, 2012).
Deming (2017) predicted individuals who will be successful in the future will able to work with
advanced technologies and noted the growing importance of social skills in the labor market.
Context of Field of Practice
New business models, advancing technologies, and socio-economic, geopolitical, and
demographic developments are accelerating the pace of change and will create opportunities for
job creation and prosperity (WEF, 2016). These changes also pose major challenges requiring
organizations, governments, societies, and individuals to adapt (WEF, 2016). For organizations
and individuals to be prepared for the future, new skills need to be developed. According to the
respondents in the WEF 2016 Future of Jobs survey, future workforce planning is a leadership
priority, with 81% of respondents recommending investing in reskilling current employees. By
2020, 35% of the skills that are predicted to be important are different than the top skills in 2015
(WEF, 2016). Chief human resource and strategy officers from global employers anticipate the
top skills in 2020 will include complex problem solving, critical thinking, creativity, people
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management, coordinating with others, emotional intelligence, judgment and decision making,
service orientation, negotiation, and cognitive flexibility (WEF, 2016). In addition to complex
problem solving, social skills including persuasion, emotional intelligence, and teaching others
will be in higher demand across industries. By 2020, organizations need to understand the impact
of advanced technologies including artificial intelligence (A.I.) on their organization and the skill
sets that their employees need in the future. Organizations need to invest in employee skill set
development in parallel to investment in technology.
This study explored large enterprise adoption, or lack of adoption, of advanced
technologies and the subsequent development, or lack of development, of their employee skill
sets. The research studied how large enterprises (organizations with 1000+ employees and over
$1billion USD in revenue) are plan to develop their employees to augment working with
advanced technologies. The research sought to understand what tasks would be completed by
advanced technologies, what tasks would be completed by employees, and the employee skill
sets needed.
Importance of Addressing the Problem
Organizations that invest in their employees’ learning and development impact individual
performance, team performance, organizational competitive advantage, and the economic
prosperity of nations (Aguinis & Kraiger, 2009). Thus, the executive responsible for leadership
and development, often titled the Chief Learning Officer (CLO), within an organization needs to
understand the impact of advanced technologies and A.I. to develop the knowledge and skills of
their employees for their organizations to be successful. For organizations to be prepared for the
impact of A.I in 2020, the organization needs a leadership and development strategy today.
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Global Goal
Given the anticipated impact of technological advancements on the future of work,
workforce planning is considered a key leadership priority for 2020 for senior executives (WEF,
2016). Therefore, the implicit goal for the industry is made explicit and anticipated that by 2020,
large enterprises need to understand the impact of advanced technologies and A.I. on their
organization and the skill sets that employees will need in the future. As organizations adopt
new technologies, the organization will need to adapt the organizational culture and the
workforce skill sets (MGI, 2017). The CLO’s knowledge, motivation and the organizational
culture will impact the organization’s ability to adapt as it adopts advanced technologies.
Stakeholder Group of Focus and Stakeholder Goal
While the contributions of all stakeholders (including the Chief Executive Officer, Chief
Financial Officer, Chief Technology Officer, etc.) impact an organization’s success, for practical
purposes, only one stakeholder group served as the focus of this study. This study focused on the
CLO of an organization. A key competency of a CLO is the ability to articulate the value of
learning in business terms (Sugrue & Lynch, 2006). Translating that value into reality requires
the CLO to lead the development of their employees. The CLO plans, designs, and creates
learning and development activities for employees to increase their capabilities and outcomes
(Douglas, 2015). The CLO is often part of an organization’s top management team and is
responsible for aligning the workers’ abilities with the organization’s strategy. CLOs need to be
able to educate their workforce on what they need to know, what they need to do, and how to be
successful in performing their jobs in the future. In effect, CLOs need to learn and educate,
transfer, and enable the transfer of learning.
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Purpose of the Project and Questions
The purpose of this project was to understand the degree to which organizations are
prepared for the impact of advanced technologies in 2020. The study focused on the CLO’s
knowledge and motivation related to creating a leadership and development strategy to develop
their workforce considering their organizations’ adoption of advanced technologies, specifically
A.I., and the interaction between organizational culture and context and CLO knowledge and
motivation. The analysis focused on knowledge, motivation, and organizational influences of
CLOs related to achieving the global goal and their specific goal.
The questions that guided the study addressed the knowledge, the motivation, and the
organizational elements for the CLO.
1. What is the CLO’s knowledge and motivation related to creating a leadership and
development strategy to develop their workforce, considering their organizations’
adoption of advanced technologies including A.I.?
Table 1
Organizational Mission, Global Goal and Stakeholder Performance
Mission
Given the anticipated impact of technological advancements on the future of work, workforce
planning is considered a key leadership priority for 2020 for senior executives.
Global Goal
By 2020, organizations will understand the impact of advanced technologies and A.I. and have
a plan to adapt their organizational culture and workforce skill sets to be successful.
Stakeholder Goal
By January 2020, CLOs will have created a leadership and development strategy to develop
the workforce of the future considering their organization’s adoption of advanced technologies
(including artificial intelligence).
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2. How does the organizational culture and context support or hinder CLO knowledge
and motivation?
3. What are the recommended knowledge and skills, motivation, and organizational
solutions?
Methodological Approach
In conducting an exploratory field research study, a qualitative research approach was
used. Qualitative research integrates theory and research with the goal of addressing important
organizational issues with organizational leaders (Coughlin & Brannick, 2014). The aim of
research is to provide the necessary information for leaders to make informed decisions to
successfully deal with the problem (Sekaran & Bougie, 2013).
Based on general recommendations for qualitative studies by Creswell (2014), this study
gathered information through interviews and document analysis. The data was gathered,
analyzed, themes formed, patterns emerged, and generalizations posed. Qualitative research
addresses the goals, the conceptual framework, research questions, methods, and validity
(Maxwell, 2013).
Contextual factors also influence research design (Maxwell, 2013). Contextual factors
that influenced this research included the perceived problems (the predictions of the impact of
advanced technologies and A.I. on the workforce of the future), the researcher’s personal goals
(to understand the workforce and skill sets needed in the future), and participant concerns (CLOs
goals to effectively develop their workforce). Recommendations are based on the comprehensive
review of literature and the analysis of the qualitative field research.
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Review of Literature
The review of literature begins with related literature of past industrial revolutions with
the remainder of the review of literature focused on A.I. and its anticipated impact on the
workplace and workforce. The purpose of the related literature is to chronicle the study of labor
and past industrial revolutions. The latter half of the review of literature shifts from the study of
labor to the advancement of technology and the impact of A.I. on employees.
Past Industrial Revolutions
Levy and Murnane’s (2012) The New Division of Labor began with a review of the study
of labor; similarly, this review of related literature provided a reflection on the past. The
economic concept of labor was developed as a result of the (first) Industrial Revolution (1760-
1820). In 1776, Adam Smith wrote The Wealth of Nations, in which he described the division of
labor as a separation of different tasks to different people to improve efficiency. By giving
workers specialized tasks, a large amount of labor was saved and generally increased
productivity. In the First Industrial Revolution, jobs were automated by machines (the steam
engine) and resulting in technical efficiency. Thus, the reorganization of work increased
productivity.
The Second Industrial Revolution (1870-1914) was sparked by the inventions of the
railroad, telegraph and machine tools. John Maynard Keynes (1933) feared, “the increase of
technical efficiency has been taking place faster than we can deal with the problem of labor
absorption” (p. 1), and therefore he predicted widespread unemployment. Keynes (1933) asked,
“What can we reasonably expect the level of our economic life to be a hundred years hence?
What are the economic possibilities for our grandchildren?” (p. 1).
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The Third Industrial Revolution also had technological progress and fears. In 1964, The
Ad Hoc Committee sent a memorandum on the Triple Revolution to President Lyndon Johnson
including similar sentiments to those expressed by Keynes 30 years earlier. The memorandum
commented on the new era of production, with a change in organizational principles triggered by
technological advancement, and the combination of the computer and automated self-regulation
machine, the, “cybernation revolution” (1964, p.1).
Indeed, almost 90 years after Keynes questioned the economic possibilities for future
workers, scholars have posed similar questions. Levy and Murname (2012) stated the division of
labor will be a division of those who can do valued work and those who cannot in a world filled
with computers. In fact, the Fourth Industrial Revolution would require rethinking education and
training. To this, Levy and Murname (2012) posed four questions: “What kinds of tasks do
humans perform better than computers? What kinds of tasks do computers perform better than
humans? In an increasingly computerized world, what well-paid work is left for people to do
both now and in the future? How can people learn the skills to do this work?” (p. 2).
The Present Industrial Revolution
Historically, scholars and individuals have feared automation and current studies
suggested technology will again impact the future of work. However, while individuals have
often feared automation, organizations have embraced automation as traditional market measures
including organizational productivity reward efficiency. Automation has historically contributed
to productivity (MGI, 2017). The opportunity for organizations is not only to increase efficiency
(i.e., doing more with less), but also innovation (i.e., doing more).
Innovation is a new method, idea, or product. Companies that want to innovate or seek
growth opportunities, often begin with observation and empathic discovery to understand what a
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customer really needs (Christensen, Anthony, Berstell, & Nitterhouse, 2007). The job to be done
concept is the, “fundamental problem a customer needs to resolve in a given situation”
(Christensen et al., 2007, p. 1). In expanding the view of a product or a service into a job,
companies can develop a deep understanding of their customers’ needs, as well as understand
other potential competitors in other industries. Companies can also consider products or other
solutions that could meet customers’ needs. Successful companies deliver on the job-to-be done
and build the right products or services for their customers utilizing both people and technology.
However, as the job-to-be-done changes, so too will the mix of how to develop the product or
solution through a combination of both people and technology.
Whereas some studies focus on the loss of employment or automation of work to
computerization (Brynjolfsson & McAfee, 2012; Frey & Osborne, 2013; WEF, 2016), other
studies focus on the need to augment skill sets as a result of technology advancement (Davenport
& Kirby, 2016; Levy & Murname, 2002). Artificial intelligence is demonstrating skills and
abilities that used to belong exclusively to human workers (Brynjolfsson & McAfee, 2012).
Often, technology is better than humans at ordinary, repetitive actions; however, computers lack
the human ability to be creative and intuitive (Brynjolfsson & McAfee, 2012). The automation of
tasks and A.I. will change work; some tasks will be completed by humans, while other tasks will
be completed by machines (or software) (MGI, 2017). Brynjolfsson and McAfee (2012) stated,
“The key to winning the race is not to compete against machines, but to compete with machines”
(p. 5). As previously mentioned, on one hand, WEF (2016) predicted that five million jobs will
be automated by 2020; on the other hand, WEF predicted that there will be an increase in
demand for new skills. To meet the demand for new skills, organizations need to reskill
employees.
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The remainder of this literature review will focus on the Fourth Industrial Revolution’s
technological advancements, specifically artificial intelligence and A.I.’s predicted impact on the
workplace and workforce. The following section included a review of the anticipated impact of
the advancement of technology and artificial intelligence on both the workplace and the
workforce. The literature review includes, the ambiguous definition of what artificial intelligence
is, the evaluation of what artificial intelligence does, and concludes with the predicted impacts of
advanced technologies on the workplace and the workforce.
A.I. Defined
The ability to define A.I. is a challenge. Even A.I. experts, developers, and employers
differ on the definition. Schank (1987) noted there was a lot of talk about A.I. and “almost
completely misunderstood by individuals outside the field” … “even A.I. practitioners are
somewhat confused about what A.I. really is” (p. 59). According to Schank, A.I. is mathematics,
software engineering, linguistics, psychology; A.I. is a bit of everything and thus lacks a clear
definition (1987). Over 30 years later, there is various definitions of artificial intelligence. While
the definition of A.I. depends upon the perspective of the author; researchers, in general, agree
on the two primary goals of A.I. one is to build an intelligent machine and to the other to find out
about the nature of intelligence.
Artificial intelligence is a fashionable technology word, a field in computer science in
which machine learning is included, and used to describe some technology product offerings.
The term A.I. was initially coined by John McCarthy in 1956. In his definition, artificial
intelligence included every aspect of learning, and other features of intelligence, and stated those
learning elements were so well documented that a machine could emulate the learning. In an
article for Forbes, Marr (2018) noted A.I. definition origins and commented that A.I. is often
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described as strong or weak. Strong A.I. systems think exactly like humans do, whereas, weak
A.I. systems determine how human reasoning works or uses human reasoning as a model, but not
the end goal (2018). A final key subset of A.I. is the term, and field of, machine learning.
Machine learning is dedicated to solving cognitive problems commonly associated with human
intelligence, such as learning, problem solving, and pattern recognition. Marr highlighted several
leading technology companies have developed and defined A.I. differently. For Amazon,
“without ML (machine learning) amazon.com couldn’t grow its business, improve its customer
experience and selection, and optimize its logistic speed and quality” (2018, p.1). Google, and
it’s A.I. division, is comprised of machine and deep learning with a goal of creating smarter,
more useful technology and help as many people as possible. Facebook has an A.I. research arm
with the goal of advancing the field of machine learning and creating new technologies to give
people better ways to communicate. Indeed, artificial intelligence is a growing field with experts
seeking to get clarity on the definition and companies attempting to develop and productize
offerings.
What Artificial Intelligence Can Do
As of 2018, machine learning has enabled automation of routine tasks, but it is beginning
to take on more human tasks once thought too difficult to automate. Brynjolfsson and McAfee
(2012) noted advanced technologies have demonstrated skills and abilities that used to belong
exclusively to human workers and while technology is often better than humans at ordinary,
repetitive, actions, computers lack the human ability to be creative and intuitive. Before, it was
perceived machines were often better than humans at repetitive actions; however artificial
intelligence technology has evolved to be able to do more human tasks (from drive a car to
develop its own language). Many companies have machine learning product offerings in the
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market. Additional product examples include Apple’s Siri, a voice-activated computer that
people interact with for directions, to dial a number, to send a text message, to read a text
message; to Amazon’s Alexa a voice-activated assistant, which when activated on command can
answer questions, play music, set an alarm, tell time, and is gaining more ‘skills’ regularly. A
final example of advanced technologies includes, Tesla, a car that has self-driving and predictive
capabilities.
Adoption of A.I. Impacts Organizational Culture, Mindsets, and Skill Sets
Artificial intelligence promises benefits, but organizations and employees need to adapt
as they adopt advancing technologies. McKinsey (MGI) recommends the organizational culture
must support collaboration of humans and machines and that trust is key (2017). In the adoption
of new technologies, to build trust, McKinsey recommended companies communicate with
employees and address any concerns and employees have about working with advanced
technologies as the adoption of the technology will require many employees to reskill.
Collaboration with machines will require reskilling or redeploying employees; therefore,
employees need to be prepared for a lifetime of reskilling. McKinsey estimated 60% of all
occupations will have at least 30% of technically automatable activities including, physical tasks
in highly structured and predictable environments, as well as, data collection and data processing
(2017). Organizations and workers need new skills, mindsets, and culture.
Artificial intelligence has the ability to automate many tasks and automation leads to
adjustments in the workplace. While there is some fear around automation, other experts note
how machines will complement people (Autor, 2015; Brynjolfsson & McAfee, 2012; Davenport
& Kirby, 2016). Indeed, people and machines together have increased output and results leading
to higher demand for specific skills (Autor, 2015). Thus, changes in technology alter the types of
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work available, skills needed, and what those types of skills pay. Levy and Murname predicted
problem solvers would be valued in the market; people who could solve unstructured problems,
work with new information, and do non-routine work (2012). The World Economic Forum
predicted new skills (including problem solving) are becoming more important and that by 2020,
more than a third of the desired core skill sets of most occupations will be comprised of skills
that were not considered crucial in 2016 (2016). Artificial intelligence development and adoption
will require organizations and individuals to adapt.
Chief Learning Officer Knowledge, Motivation and Organizational Influences
To research the impact of advanced technologies on the workplace and the workforce, the
Clark and Estes (2008) gap analytic conceptual framework was used to frame this study. The
Clark and Estes (2008) model is the required conceptual framework for doctoral students in the
EdD Organizational Change Leadership program at the University of Southern California
Rossier School of Education. The Clark and Estes (2008) model focused on knowledge,
motivation and organization. Using this model as a guide, the research sought to explore the
degree to which CLOs have the adequate knowledge, motivation, and organizational support to
be successful in creating a leadership and development strategy for their organizations with the
adoption of advanced technologies. The research focused on the organizational influences from
culture to resources in which the organization’s CLO operates, and the CLO’s knowledge and
motivation.
Each of the organizational, knowledge, and motivational influences as directed by the
Clark and Estes (2008) gap analysis was analyzed in the context of exploring whether
organizations are prepared for the impact of advanced technologies on the workplace and the
workforce. The CLO’s knowledge needs ranging from conceptual to metacognitive knowledge is
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covered first. Following the knowledge influences, the CLO’s motivation and self-efficacy and
emotions is discussed. Finally, the assumed organizational influences on achievement of
stakeholder goal is reviewed. The assumed external environment influences on organizational
and individual performance will be examined throughout the research.
Knowledge Influences
Artificial intelligence will influence organizational strategy and individual skill sets.
CLOs and the workforce need a range of knowledge, including factual, conceptual, procedural,
and metacognitive, to prepare the workforce of the future. Rueda (2011) defined the different
types of knowledge from factual to metacognitive. Factual knowledge is the definition, terms,
details, and contexts (the what is or the facts). Conceptual knowledge is the categories,
generalizations, and classifications (the concepts around the knowledge). Procedural knowledge
is understanding how to do something (from learning to job tasks). Metacognitive knowledge is
knowing when to do something and why to do it.
Knowledge about A.I. and how it is adopted in their organization. To prepare their
workplace and the workforce for working with advanced technologies, CLOs need factual
knowledge, including the ability to define A.I. and determine what A.I. is adopted in their
organization. Since the definition of A.I. varies, it will be important for CLOs to understand
artificial intelligence concepts (Marr, 2018; Schank, 1987). For each CLO, how they define and
understand A.I. has been adopted within their organization and may vary. However, CLOs will
need knowledge around what A.I. is and what A.I. is being employed to do to know what tasks
employees will do within their organization.
Knowledge about A.I. and what it will do within their organizations. Beyond the
factual knowledge of A.I., CLOs must be able to describe what tasks A.I. will perform within
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WORKFORCE
24
their organization and what tasks people will perform. Specifically, CLOs need to know what
tasks A.I. will perform (i.e., analyze a set of data) and determine what tasks employees will
perform (i.e., decision making). With knowledge around A.I., CLOs need to know how the
organization will develop products or services through a combination of people and technology.
By knowing how all the tasks needed to be done to complete a job and if a human or machine
will complete them, CLOs will be able to a develop leadership and development strategy related
to how their organization will prepare its employees to augment their skills to work alongside
advanced technologies.
The role of the CLO is to champion the leadership and development of their
organization’s workforce. For CLOs to be successful, they need to know about advanced
technologies, the context, the future of work, and about their employees and about themselves. In
gaining a procedural understanding around artificial intelligence, CLOs will have information
key to planning learning and development activities to help reskill their employees.
Knowledge about A.I. and how to learn about artificial intelligence. CLOs need to
understand A.I., and understand what they need to know about A.I., and how they can help
develop their workforce to work with artificial intelligence. Metacognitive knowledge will
enable CLOs to know when and why to do something (Rueda, 2011). Metacognition will be key
in helping CLOs solve problems while considering the contextual and conditional aspects of the
impact of advanced technologies within their organizations.
CLOs will also need to be mindful of their own metacognition. In understanding their
own metacognitive knowledge and cognitive load, they can have empathy for developing the
learning and development plans for their employees. CLOs are tasked with developing their
workforce, so they need to understand how to prepare their workforce as their organization
THE IMPACT OF ADVANCED TECHNOLOGIES ON THE WORKPLACE AND THE
WORKFORCE
25
adopts advanced technologies. Individuals need to know what knowledge to have to successfully
carry out this task, how to approach this task, and what they can do to change learning strategies
for themselves and others, if difficulties arise (Baker, 2006).
Table 2
Chief Learning Officers Knowledge Type and Knowledge Influence
Knowledge Type Knowledge Influence
Conceptual CLOs need to be able to define A.I. and understand what
advanced technologies are being employed within their
organizations.
CLOs need to know what tasks will be completed by A.I. to
understand what tasks will be completed by employees.
Procedural CLOs need to know what skill sets employees need (complex
problem solving, critical thinking, cognitive flexibility,
mathematical reasoning and active learning) to be successful in
the workplace in working with machines and how to develop
them.
Metacognitive CLOs need to know what they know about A.I., understand
what they need to know about A.I., and how they can help
develop their workforce to work with artificial intelligence.
Motivation Influences
Motivation is important at work in driving individuals to reach their goals. For CLOs to
learn and work with advanced technologies, they need motivation. Motivation to choose to work
towards the goal and motivation to persist and not be distracted during the goal pursuit will
require mental effort (Clark & Estes, 2008). Two motivational concepts that the study explored
with CLOs are emotions and self-efficacy.
Staying positive and hopeful about the adoption of artificial intelligence. Emotions
can be positive or negative, activating or deactivating and affect effort, motivation to persist, and
strategies for learning and cognitive concepts (Pekrun, 2011). CLOs need to use their self-
awareness to self-regulate their emotions, and their workforce’s emotions, around the topic of
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WORKFORCE
26
A.I. to persist in their learning and in the development of their employees. Even among A.I.
experts, the topic of artificial intelligence can induce a range of emotions. Mark Zuckerberg
contends that A.I. could help solve some of humanity’s greatest problems (Dowd, 2017). Articles
have cited thought leaders, including Elon Musk and Stephen Hawking, whom each have argued
A.I. would end the human race (Dowd, 2017; Cellan-Jones, 2014). Depending on if you see A.I.
as an opportunity or threat, A.I. could elicit potentially positive activating emotions of hope,
pride and enjoyment, or potentially negative emotions of anger, anxiety, frustration and
hopelessness. The battle between the dichotomous emotional experiences of hope, pride and
enjoyment versus anger, anxiety, and frustration, may force CLOs and their employees to
reexamine how their emotions impact their work with advanced technologies. CLOs need to
ensure that they and their workforce remain persistent in learning; how to work with machines
and augment their skill sets while not feeling hopeless (negative deactivating) against working
with advanced technologies is a significant concern that must be addressed. If CLOs, or
employees, have negative emotions, especially deactivating (hopelessness), it will be difficult to
develop the knowledge needed to be successful, or possibly even employed. CLOs and
employees need to believe they can be successful and be excited about working with advanced
technologies to gain the knowledge needed to be a valued employee in the Fourth Industrial
Revolution.
Self- efficacy to develop employees for future work with artificial intelligence. Self-
efficacy is the self-perception an individual has about their capability to perform a specific task
(Pajares, 2006). If CLOs do not believe they can develop their employees for the future of work
with A.I., the CLO will struggle with persisting and investing the necessary mental effort to
successful. Self-efficacy will be important for CLOs to persist and regulate their own actions and
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WORKFORCE
27
cognitions around advanced technologies and to prepare their workforce to work with advanced
technologies.
Table 3
Chief Learning Officers Motivation Type and Motivation Influence
Motivation Type Motivation Influence
Emotions CLOs should be excited about the future of
work and prepared for the impacts of A.I.
Self-Efficacy and Collective
Efficacy
CLOs need to believe they and their
organizations are capable of effectively
developing a leadership and development
strategy to work with advanced technologies.
Organizational Influences
Behaviors are a function of a person in his or her environment (Lewin, 1936). The external
environment can influence individual and organizational performance and the organization can
influence skill sets and motivations (Burke & Litwin, 1992; Clark & Estes, 2008). Schein (2004)
noted that there are many cultures that come to shape an organizational culture. Organizational
culture, and how the organization works, impacts how a manager leads and influences employee
behaviors (Burke & Litwin, 1992). The organizational cultural model emphasized culture is both
what people say about the organization and how people work in the organization (Schein, 2004).
Schein (2004) further extrapolated an organizational culture into three levels: artifacts (the visual
organizational structures and processes), espoused values (strategies, goals, philosophies), and
basic underlying assumptions (unconscious, taken for granted beliefs, perceptions, thoughts and
feelings, ultimate source of values and action). Gallimore and Goldenberg (2001) posit that
culture can be separated into cultural models and cultural settings. They defined cultural models
as shared mental schema or understandings of how the world works, including values and group
dynamics (Gallimore & Goldberg, 2001). Cultural models are often invisible and unnoticed.
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WORKFORCE
28
Cultural settings include the location and occasion where people come together to carry out joint
activity that accomplishes something they value (Gallimore & Goldberg, 2001). Individual
knowledge and motivation will be keys for individual and organizational success.
Organizational model. Advancements in technology impact both organizations and
individuals. The impact of advances in technology will require a change in organizational
cultures. Organizational cultures need to be open and collaborative while reskilling the
workforce (MGI, 2017). Organizations need cultural models of psychological safety and identify
as a learning organization (Edmonson, 1999; Senge, 1990). Group dynamics are considered part
of the cultural model (Gallimore & Goldberg, 2001). Group dynamics can influence knowledge,
motivation and behavior (Noumair, Pfaff, St. John, Gipson, & Brazaitis, 2017)
Psychological safety. Psychological safety has a positive influence on organizational learning
and performance. Psychological safety described an environment where employees have
interpersonal trust, mutual respect and are, “comfortable being themselves” (Edmonson, 1999, p.
2). The concept of team psychological safety is a shared belief by team members that it is safe to
take risks in the group (Edmonson, 1999). Edmonson’s research demonstrated team
psychological safety is associated with learning behavior. For employees to learn a new way of
working, the organizational culture must be one of psychological safety (Edmonson, 1999).
Similarly, Carmeli, Brueller, and Dutton (2009) highlighted the importance of quality
relationships in the workplace for cultivating and developing perceptions of psychological safety
and learning behaviors. Kostopoulos and Bozionelos (2011) found that 1) there was no-tradeoff
between team exploratory and exploitative learning, 2) evidence against the ambidexterity
premise as exploratory and exploitative learning do not interact, but constitute two different
(additive) sources of team performance, 3) psychological safety is a key antecedent of team
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WORKFORCE
29
learning related to learning activities of innovation project teams, and finally, 4) evidence that
task conflict enhanced the beneficial effects of psychological safety on team learning activities.
A psychologically safe organizational culture is vital for employees to exhibit learning
behaviors. Psychological safety must be present before teams can learn and innovate.
Learning organization. A learning organization promotes learning and is continuously
transforming (Senge, 1990). A culture of organizational learning occurs when employees can
expand their capability, new patterns of thinking are encouraged, and people are continually
learning how to learn together (Senge, 1990). Beyond a learning organization in theory,
Kiedrowski (2006) studied the impact of learning organization concepts on job satisfaction and
found employee satisfaction increased with the acceptance of learning organization concepts.
Thus, becoming a learning organization may be necessary because of the rapidly changing
external environment, but also is worth investment for the competitive advantage of employee
satisfaction.
Group dynamics. While the external environment influences the knowledge needed in
organizations, group dynamics within organizations can also influence knowledge and
motivation. Noumair et al. (2017) built upon the Burke-Litwin Model to examine what is beneath
the boxes and reviewed how overt behavior of individuals, systems, and groups are linked to
covert dynamics. In relation to this study on organization, knowledge and motivation, group
dynamics can the impact individual knowledge. For instance, some employees could hide or
overstate their knowledge on the topic and motivation. As per social cognitive theory, human
functioning is rooted in social systems, and thus to understand an individual’s knowledge and
motivation, the study must also understand the resources and opportunity structures within an
organization for personal development and function (Bandura, 2005). While this study focused
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WORKFORCE
30
on organizational cultural models and settings and the CLO’s knowledge and motivation, the
researcher was cognizant of group dynamics, and that organizational culture and social systems
can impact individual knowledge and motivation.
Organizational setting. Gallimore and Goldberg (2001) included in cultural settings the
location and occasion where people come together to carry out joint activity that accomplishes
something they value. The Burke-Litwin Model (1992) found there are links between
organizational culture (cultural model) and systems, leadership, management practices, work unit
climate, and structure (cultural setting). If the organizational model needs to embrace learning
and adaptability, the cultural settings from leadership to systems, policies, and procedures to the
office environment needs to change as well.
Transformational leadership. According to Kumako and Asumeng (2013),
transformational team leadership is an important variable in a team member’s perception of the
team as psychologically safe enough environment to engage in learning behaviors. The 2013
study indicated a positive relationship between team psychological safety and team learning
behavior, with transformational team leadership moderating this relationship. For an organization
to be a place of learning, it must have a culture and leaders that make employees feel it is a safe
place to learn and experiment.
Resources. Leadership is important for modeling behaviors and creating a safe
environment. As the large enterprises in the WEF study (2016) identified, there is a need for new
skills in the future of work. For CLOs, their task of developing new skills is something that will
require new knowledge and motivation on their parts, but also resources (budget, staffing) from
the organization. This research explored whether, and to what degree, organizations have
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WORKFORCE
31
provided budgets and resources for leadership and development as the organization adopted new
technologies.
Organizational cultural models and cultural settings influence behaviors. The focus of
this research examined cultural models around psychological safety and organizational learning.
The research also explored the cultural settings around transformational leaders and resources.
Table 4
Organizational Influences
Organizational Influence Type Organization Influence
Cultural Model Organizations need to create a culture of psychological
safety for employees to learn new ways of working.
Cultural Model Organizations need to create a culture that values
organizational learning.
Cultural Setting Organizations need to provide CLOs with resources (i.e.,
budgets) so they can plan and create professional
development offerings on how to work with advanced
technologies.
Conceptual Framework: The Interaction of Chief Learning Officers’ Knowledge,
Motivation and the Organizational Context
The conceptual framework is a combination of the literature review and the study
questions. This study focused on knowledge, motivation, and organizational influences of Chief
Learning Officers (CLOs) related to creating a leadership and development strategy for their
workforce considering their organization’s adoption of advanced technologies. The aim was to
provide the necessary information needed for leaders to make informed decisions on preparing
their organizations and workforces for the impact of artificial intelligence.
A constructivist worldview was used to understand the impact of the external
environment on organizations from multiple organizational contexts. Using qualitative methods,
CLOs were interviewed and document analysis conducted to make recommendations for large
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WORKFORCE
32
enterprises. The research was broad and explored the knowledge, motivation, and organizational
influences of CLOs to construct meaning of the impact of advanced technologies on the
workplace and the workforce.
The conceptual framework was influenced by the Burke-Litwin (1992) model, which
explored the external environmental influences on organizational mission, leadership, and
culture. The Burke-Litwin model complimented the Clark and Estes (2008) framework which
guided the study. The conceptual framework is depicted in Figure 1.
Figure 1. The external environment and the impact on industry, organizational context, and
CLO’s knowledge and motivation.
The external environment and the impact of advancements in technology, particularly the
adoption of artificial intelligence will have a direct influence on industries, organizational goals,
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WORKFORCE
33
and individual skill sets. This study examined the investments in technology and employee
development and the impact on the organization. An evaluative field research study was
conducted, including multiple large enterprises to understand how the external environment
impacted the organizational goals, cultural context and models, and influenced the CLOs within
their organization in preparing their workforces for the future. The study explored organizational
culture models and culture settings. Schein’s (2004) concept on organizational culture was
utilized and explored through document analysis (espoused values and artifacts) and interviews
(basic assumptions). Organizationally, the study sought to understand if the CLO perceives that
s/he is operating within a culture of psychological safety and organizational learning, and if the
CLO perceives that s/he has the resources needed to be successful.
It is important to note that the organization and the CLO have a bi-directional relationship
as the organization influences the CLO and the CLO influences the organization in planning for
the future of work. The CLOs’ knowledge as it related to conceptual, procedural, and
metacognitive knowledge around the impact and adoption of A.I. was examined. The research
also analyzed the organizational culture and context, including resources and psychological
safety in preparation for the future of work. Through the presented conceptual framework, it was
hypothesized that the external environment and the adoption of advanced technologies. would
influence organizational strategy and individual skills needed. To be successful, CLOs need a
range of knowledge and motivation.
Participating Stakeholders: Sampling and Recruitment
As described in the conceptual framework, this study focused on Chief Learning
Officers’ (CLOs’) knowledge, motivation, and organizational influences related to creating a
leadership and development strategy in the context of their organization’s adoption of advanced
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WORKFORCE
34
technologies. The participating stakeholders sampling and recruitment strategy was designed to
identify and connect with the executives tasked with developing leadership and development
strategy within large enterprises. Once the interview was scheduled, publicly available
documents were reviewed in preparation for the interview, which provided additional data to
answer the research questions.
Sampling Criteria and Rationale
Criterion 1. The first selection criterion for the sample was that the company must be a
large enterprise (1000+ employees with revenue over $1billion USD). The rationale for this
criterion is that a larger organization is more likely to have an executive focused on workforce
development.
Criterion 2. The second criterion for the sample was for the individual responsible
within the organization to develop their workforce (typically the chief learning officer or head of
leadership and development).
Sampling Strategy and Rationale
Nonprobability sampling aims to discover what is occurring and those implications
(Merriam & Tisdell, 2016). A nonprobability approach to sampling versus a probability sampling
was utilized for this study, noting that the results of the study from the sample to the population
will not be generalizable (Merriam & Tisdell, 2016). The purposeful, nonprobability sampling
approach promoted discovery, understanding, and gain insight from a sample from which the
most can be learned (Merriam & Tisdell, 2016). A network approach allowed this researcher to
connect with professional contacts within large enterprises, and gain introduction to the CLO
within said organizations. Utilizing a snowball sample approach, the objective was for
researched subjects to refer other subjects for interviews (Merriam & Tisdell, 2016). The goal
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WORKFORCE
35
was to conduct a minimum of six in-depth qualitative interviews with CLO executives from
organizations of large enterprises; a total of seven interviews were completed. Given the nature
of this qualitative research was to discover and understand, the focus was on more in-depth
quality interviews instead of a specific quantity of respondents. Additional data of the large
enterprises participating in the interviews (and following the sampling criteria) was collected
through documents and artifacts.
Explanation for Choices
The qualitative approach allowed for in-depth conversations with participants, analysis of
documents, and met the research goals of the study to discover, understand, and gain insight into
what the CLO was doing to prepare his/her workforce for 2020. The benefits of interviews was
to have an interpersonal encounter; a conversation with a purpose (Merriam & Tisdell, 2016). A
semi-structured interview approach was used, with a guide to address the research questions and
areas to explore the CLOs’ knowledge, motivation, and organizational influences. The semi-
structured interview format allowed for exploration of what the CLO has done to prepare for the
impact of advanced technologies on workforce development.
Data Collection and Instrumentation
In qualitative research, researchers state questions versus objectives or hypotheses and
assume the form of a central question (Creswell, 2014). The central qualitative question for
CLOs was how they are preparing their workforce for the future and the anticipated impact of
advanced technologies (and artificial intelligence) within their organizations. The study explored
the CLOs’ knowledge and motivation related to creating a leadership and development strategy
to develop their workforces, as well as the interaction between organizational culture and context
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WORKFORCE
36
on CLO’s knowledge and motivation. The qualitative data was collected through interviews and
document analysis.
The interviews with CLOs were scheduled at times and locations convenient for the
participants. The interviews were conducted over the phone. Copious notes were taken during
the interviews.
Interviews
Interview protocol. The qualitative data was collected through semi-structured
interviews. These interviews focused on understanding the current state of CLO leadership and
development strategy planning for their workforce in 2020. The goal for the research was to
conduct qualitative research with CLOs from large enterprises.
Interview procedures. The interviews were held per the participants’ preference either
virtually via an online platform, over the phone, or in-person at a location of their choosing
(Rubin & Rubin, 2011). The formality and tone of the interview was based on the context and
rapport with the participant. Copious notes were taken throughout the interview via computer
(Merriam & Tisdell, 2016).
Documents and Artifacts
Documents are another source of data in qualitative research (Merriman & Tisdell, 2016).
The documents collected were reviewed for information related to the organization’s mission,
vision, strategy and culture. Additionally, the researcher reviewed the LinkedIn profiles of all of
the research participants.
Document analysis procedures. Documents reviewed were related to the interviewed
participant’s and each participant’s company. A review of publicly available documents occurred
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WORKFORCE
37
in advance of the scheduled interviews. Documents included websites, LinkedIn profiles, annual
reports and press releases.
Data Analysis
Qualitative analysis is inductive, and the researcher searched for themes, patterns, or
categories emerged from the data (Merriman & Tisdell, 2016). The data set consisted of
transcribed interviews and publicly available documents. Data analysis was managed and
organized using Atlas.ti software. The software was used to search content, link concepts, and
map emerging themes. Prior to analysis, a codebook in Atlas.ti with a priori codes was
developed, focused on the conceptual framework. Additional empirical codes were added as the
data set was analyzed. Analytic tools and strategies recommended by Corbin and Strauss (2008)
were used, including the use of questioning, looking at what emotions (or lack of emotions)
expressed, and thinking in terms of metaphors and similes. Analytic memos were also written
throughout the experience to note both potential research themes and self-reflection.
Results and Findings
The goal of this project was to understand the degree to which organizations are prepared
for the impact of advanced technologies in 2020. The qualitative research addressed the goals,
the conceptual framework, and the research questions. As noted, the conceptual framework was
influenced by the Burke-Litwin (1992) model, which explored the external environmental
influences on organizational mission, leadership, and culture. The Burke-Litwin model also
complemented the Clark and Estes (2008) framework that explored the knowledge, motivation,
and organizational influences of identified stakeholders. The study focused on the CLO’s
knowledge and motivation related to creating a leadership and development strategy to develop
their workforce considering their organization’s adoption of advanced technologies, specifically
THE IMPACT OF ADVANCED TECHNOLOGIES ON THE WORKPLACE AND THE
WORKFORCE
38
A.I., and the interaction between organizational culture and context and CLO knowledge and
motivation.
Using qualitative methods, CLOs were interviewed and a document analysis conducted to
make recommendations for large enterprises. The research was broad and explored the
knowledge, motivation, and organizational influences of CLOs to construct meaning of the
impact of advanced technologies on work. Interviews were conducted over the phone (due to the
preference of all the participants) and copious notes were taken. All potentially identifying
information surrounding the participant and their respective organization was removed to protect
individual and organizational confidentiality and privacy.
Research Questions
The questions that guided the study addressed the knowledge, the motivation, and the
organizational elements for the CLO.
1. What is the CLO’s knowledge and motivation related to creating a leadership and
development strategy to develop their workforce, considering their organizations’
adoption of advanced technologies including A.I.?
2. How does the organizational culture and context support or hinder CLO
knowledge and motivation?
3. What are the recommended knowledge and skills, motivation, and organizational
solutions?
Participating Organizations and Stakeholders
The participants of this study represented a variety of large enterprises (as defined in the
sampling criteria as organizations with 1000+ employees with revenue over $1billion USD).
Table 5 provides an overview of the large organizations of which their CLO (or equivalent in
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39
title, the individual responsible within the organization for developing their workforce)
participated.
Table 5
Participating Organizations and CLOs
Industry Number of Employees Participant * CLO
Financial Services > 50,000 CLO 1
Financial Services > 75,000 CLO 2
Financial Services >250,000 CLO 3
Technology
Services
>200,000 CLO 4
Technology
Services
> 90,000 CLO 5
FinTech > 1,000 CLO 6
Financial Services > 45,000 CLO 7
Note. * Codes replaced actual names.
Additional data from the large enterprises participating in the interviews (and following
the sampling criteria) was collected by the researcher from publically available documents and
artifacts (including websites, annual reports and press releases) to further analyze the
organizational culture. Conversations with each CLO, coupled with the document analysis of
their organizations, constructed the following findings and themes. While seeking answers to the
three primary research questions, four findings with supporting themes emerged.
Finding 1: CLOs Report to be Knowledgeable about the Future of Work
Interviews determined that CLOs report knowledge on how to create a leadership and
development strategy to develop their workforce, while considering their organization’s adoption
of advanced technologies, including artificial intelligence. The researcher anticipated a need to
understand more about the tasks that advancing technologies were completing within the
organization (conceptual and procedural knowledge needs). Based on the World Economic
Forum’s (2016) call for targeted action to build a workforce with “futureproof skills” (p. 11) to
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40
balance the influence of technological, demographic, and socio-economic changes, it is projected
that five million jobs worldwide will be automated by 2020. However, given that A.I. is still in
development, the large enterprises identified in this study reported that vast automation has not
occurred. While widespread impact of advancing technologies has not disrupted the large
enterprises in this study, the CLOs were focused on investing in developing more life core skills
for their workforce.
The first finding answers the first research question posed in the study. The first question
focused on the CLO’s knowledge and motivation related to creating a leadership and
development strategy to develop his/her workforce, considering their organizations’ adoption of
advanced technologies including A.I. The interviews explored the CLOs’ conceptual, procedural,
and metacognitive knowledge as noted in Table 2. The assumed conceptual knowledge explored
if CLOs could define A.I. and understand what advanced technologies were being employed
within their organization, and conceptually know what tasks therefore would be completed by
A.I. to understand what tasks would be completed by employees. The research explored CLOs
procedural knowledge and specifically what skill sets employees needed to be successful in the
workplace in working with machines. Finally, the research explored CLOs metacognitive
knowledge around advanced technologies. and knowing what they needed to know (and how to
learn it) to help develop their workforce for the future. Interviews with CLOs revealed that CLOs
have conceptual, procedural and metacognitive knowledgeable. The finding that CLOs are
knowledgeable about the future of work is supported by three themes.
CLOs report to know A.I. is coming and machine learning is here. In interviews, the
CLOs demonstrated conceptual knowledge on A.I. and advanced technologies. CLO 1 noted, “it
will be some time before A.I. can reason and have a level of intuition.” Indeed, artificial
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41
intelligence is still in development, while machine learning, a subset of artificial intelligence, is
in organizations today. CLO 6 commented, “the art of machine learning and looking at patterns
will benefit the organization in many ways.” CLO 3’s comments echoed this sentiment:
We are experimenting with machine learning. A.I. at its very core and will require us how
we change how we do work in the future and change the nature of our workforce as well.
Our focus in looking at A.I., or robotics, or big data, or other types of digital capabilities
are directly correlated to what is the problem we are trying to solve. More specifically,
the commercial impact for developing that. As we test those new capabilities, we test
with an end in mind to address a specific issue.
As CLO 1 concluded, “we are building the fundamentals and the structures for when we,
and A.I., are mature enough, we can take advantage of the technology.”
CLOs report to know they must develop adaptability. In interviews, the CLOs
demonstrated procedural knowledge by discussing the skill sets their employees needed to be
successful in the workplace of the future. One key skill set CLOs are looking to develop or hire
into their organization is adaptability. Several CLOs noted they were looking for people with
adaptability. CLO 2 commented they were building core skills that were difficult to hire in the
market the core skills included leadership, adaptability and collaboration, “you can’t predict the
nature of jobs, but core skills where man and machine meet.” CLO 5 noted, “we want people to
adapt and flex to what’s next. Today it might be python, then blockchain.” CLO 6 posited:
We aren’t planning for 2019. We are planning for five years from now and want people
who are smart, able and adaptable, and flexible. We want people who have learning
agility, flexibility, openness, and a personality composition where it’s easier to be
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42
flexible. We want our organization to have internal mobility structures, where they could
go do something else.
As CLO 2 voiced, “if we believe jobs fundamentally change every 2-3 years, then we
want adaptability skills.” This theme supports the finding that CLOs understand how to develop
their workforce for the future.
CLOs report to have self-awareness on advanced technologies, key for
metacognitive knowledge during change. The final theme supports the finding that CLOs have
knowledge and specifically, have metacognitive knowledge. This knowledge is acquired through
the process of metacognition which is gained through reflection and self-awareness. The CLOs
interviewed demonstrated self-awareness which is a component of metacognitive knowledge.
Metacognitive knowledge includes, “knowledge of general strategies that might be used for
different tasks, knowledge of the conditions under which these strategies might be used,
knowledge to which the strategies are effective, and knowledge of self” (Pintrich, 2002, p. 1). A
key component of metacognitive knowledge is self-awareness of which two CLOs specifically
discussed both in theory and in practice. CLO 6 discussed the importance of being a reflective
practitioner and how being reflective can build awareness and capacity. In the interview with
CLO 1, they also discussed the importance of self-awareness and helping his workforce know
‘who they are’ and think about their goals and how to achieve them. The acknowledgement of
self-awareness in support of building knowledge supports their metacognitive knowledge. In
addition, the CLOs identify as lifelong learners through formal education and informal learning.
A document analysis of the participating CLO’s LinkedIn profiles revealed that all participants
had post-graduate degrees. In addition, a majority of the participants had completed or were
enrolled in doctoral programs.
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Regarding knowledge about the future of work and advancing technologies, many CLOs
referred to sources including reading Harvard Business Review, World Economic Forum reports,
utilizing external advisors and consultants including McKinsey, and talking to their
organization’s heads of technology to see what technologies their organization was adopting.
CLO 5 noted they, “read a ton” including the World Economic Forum reports, The Economist
and the Wall Street Journal, and also connect the learning to the world through social
connections. The CLO went on to state, “to get yourself ready for career longevity, you need to
be lifelong learning; every week you need to learn an hour of something new.”
Finding 2: CLOs Report to be Motivated to Prepare their Workforce for the Future
Interview findings demonstrated that CLOs are motivated to create a leadership and
development strategy to develop their workforce considering their organization’s adoption of
advanced technologies. The second finding answers the first research question posed in the
study. The first question focused on the CLOs’ knowledge and motivation related to creating a
leadership and development strategy to develop their workforce, considering their organization’s
adoption of advanced technologies, including A.I. The interviews explored the CLOs’ motivation
around emotions and self-efficacy as noted in Table 3. Interviews with CLOs revealed that
CLOs express positive emotions around advancing technologies and feel confident in their
ability to prepare their workforce for the future. The finding that CLOs are motivated is
supported by two themes discussed next.
CLOs report to feel positive about the potential of artificial intelligence. The research
explored CLOs’ feelings around A.I. As noted in the motivational influences section emotions
impact effort and strategies for learning (Pekrun, 2011). While A.I. can elicit a range of
emotions, the CLOs interviewed expressed positive (activating) emotions that will be key in
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44
being successful in their role and with their goal of preparing their workforce for the future of
work.
The participating CLOs expressed positive feelings around the potential of artificial
intelligence in the workplace. A majority of CLOs see A.I. as an enabler of their workforce and
their organization. However, their sentiment was balanced with the appreciation that while they
may have positive feelings about advancing technologies, their workforce may not feel the same.
As CLO 4 asserted, “leaders need to provide reassurance and comfort to their workforce for
employees to not fear losing their jobs to automation, but embrace technology and learn new
skills.” CLO 2 mentioned that “leaders need to help their workforce have confidence in working
with new technologies.”
The adoption of new technologies is not new for organizations. For years, organizations
have focused on rolling out new technology, from iPads to machine learning, in an effort to be
efficient and effective. Organizations have learned how to help their workforce prepare for the
future. CLO 2 described a learning from a past technology adoption. The CLO described that the
organization needed to identify champions within the workforce to help build the confidence of
others, “we did the biggest iPad order ever and yet we found half were just sitting in the box in
the office unopened.” Once the organization realized the iPads were not being used, they created
change champions. The organization found people passionate about digital and made them the
change champions within the organization to help others gain confidence in using new
technology. For artificial intelligence, the organization plans on developing and supporting A.I.
champions within the organization. The organization has also required leaders to demonstrate
knowledge in the area of digital literacy for promotion.
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CLOs report to have self-efficacy, but lack collective-efficacy. Self-efficacy is the
self-perception an individual has to perform a specific task (Pajares, 2006); whereas collective-
efficacy is the feelings an individual has about the group’s ability to be successful (Bandura,
2000). All interviewed CLOs demonstrated self-efficacy as they feel confident in their ability to
prepare their workforce for the future. However, some CLOs question whether their
organizations at the micro level, and society at the macro level, will be as successful.
CLO 5 indicated a belief that they were prepared, knowledgeable, and motivated for the
future, but stated her organization was not. At the organizational level, CLO 5 discussed a
disconnect between their organization’s statements and actions. Despite the organization’s
external statement on its desire to prepare the world (with the skill sets individuals need) for the
future of work, the CLO countered, arguing that the actions did not match the sentiments:
I see people talking a lot about the future of work, but I don’t see any kind of coordinated
effort. I talk about it and I feel like I’m going uphill. I don’t feel supported in the journey
that I have been taking the company on. A.I. is a bright shiny object that people are
talking about, but it hasn’t translated into action. There isn’t consistent programs,
policies, procedures or approaches. There is a great sense of urgency, but the inertia to
change is too large.
CLO 6, while knowledgeable and motivated, saw advanced technologies as both an asset and a
threat to society, “I think we will see radical changes in how we work and live.” CLO 6 went on
to wonder about, “the wars of the future will be information wars and covert actions and yet
many still think of war in a glorified WW2 frame, with people in trenches and front line. I don’t
think the US is ready for that.” CLO 3 also saw advanced technology as an opportunity and
threat and commented that as an organization, they believed they were well prepared, but
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questioned the preparation of schools and businesses. “We see it already as we look at income
inequality which is being driven by these capabilities ….We have barely seen the tip of the
iceberg and the societal issues will only get larger as things (technology) matures,” said CLO 5.
CLOs believe they are preparing their workforce for the future of work and demonstrate
self-efficacy. While the CLO believed in themselves, many worry about other groups. Some
CLOs have questions about whether their workplace or society is prepared for the future of work,
impacting their belief in the collective-efficacy.
In general, CLOs have the conceptual and metacognitive knowledge, self-efficacy and
positive emotions around the future of work and the impact of advanced technologies on their
workplace and workforce, but there were some disconnects between the knowledge and
motivation and the organization. The CLO has the K (knowledge) and the M (motivation), while
the organizational cultures and contexts both support and hinder the CLO’s ability to make an
impact.
Finding 3: Organizational Culture and Context Impacts CLOs’ Capacity to Develop the
Workforce for the Future
While all organizational cultures studied espoused support for learning, few demonstrated
they were learning organizations with psychologically safe environments. While some
organizations provide resources to their CLO, other CLOs need to gather them. The third finding
addresses the second research question used for the study, which asked how the organizational
culture and context supports or hinders CLO knowledge and motivation. The interviews with
CLOs and document analysis of their organization’s publicly available information examined the
organizational influences of cultural models and cultural settings as noted in Table 4.
Specifically, the research examined the organizational models surrounding organizational
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learning, psychological safety, and the organizational setting concerning resources. Senge (1990)
noted a learning organization promotes learning and is continuously transforming. allowing for
employees to expand their capability; a place where new patterns of thinking are encouraged and
people are continually learning how to learn together. The concept of psychological safety is
associated with learning behaviors. Psychological safety is a shared belief by team members that
it is safe to take risks in the group (Edmonson, 1999). For a CLO to be successful in achieving
the stakeholder goal, the CLO needs resources. The CLOs interviewed and documents analyzed
revealed organizational models and settings both support and hinder CLO’s knowledge and
motivation. Supporting the finding organizational culture and context can influence CLOs
knowledge and motivation, four themes emerged.
CLOs report to believe their organizations have knowledge about advancing
technologies, but for some CLOs, they note a cultural dissonance. While a majority of the
organizational documents show knowledge of and demonstrated commitment to the future of
work, the interviews revealed that while the organization may have the knowledge, the CLO
does not think the organization may be taking enough action. CLO 5 stated, “Organizationally,
we are not preparing our company or employees for artificial intelligence.” While most
organizations have an external commitment to the future of work, that commitment did not
always translate to an organizational cultural model of organizational learning or psychological
safety, or an organizational cultural setting in which the CLO was provided resources.
CLOs report to find their organizations to be on the path to being learning
organizations. Senge (1990) defined a learning organization as one that promotes learning and is
continuously transforming. In analyzing the publicly available documents of the participating
CLO’s respective organizations (websites and annual reports), the documents demonstrate
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organizational knowledge of advancing technologies. Most 86% (six of the seven) organizations
mentioned innovation and different types of advanced technologies (including A.I., blockchain,
machine learning and the internet of things) on their websites. Regardless of industry, websites
featured content on bitcoin, block chain, the development of artificial intelligence, and digital
transformation. In addition, all websites of the participating CLO’s organization mention
learning in helping their employees grow and develop. Some organizations’ websites featured
content on how they (as an organization) hoped to help the world address the skills gap that is
being influenced by advancing technologies. However, while the websites of most (six of seven)
of the organizations featured content about advancing technologies, the future of work, learning
and reskilling, beyond the statements some organization’s CLO commented they saw various
levels of organizational commitment to the future of work.
The documents analyzed, as noted, demonstrate the organization’s awareness of
advancing technologies, the future of work and a statement on learning; however, not all of the
organizations by definition are learning organizations. While a learning organization promotes
learning it is also an organization that transforms (Senge, 1990). The organizations are stating
that they know about the impact of advanced technologies, and a majority of the organizations
are beginning to transform. A majority, 57%, (four) organizations noted the impact of advancing
technologies in their business strategies and have committed to transforming their organizations
as demonstrated by the hiring of new leadership. Some leaders have even been hired into
organizations with the title of Head of Transformation. Another organization demonstrated its
knowledge about advancing technologies through its stated commitment to preparing the world
for the future on its website, and yet that organization’s CLO does not believe the organization is
taking enough action. Interviews with CLOs confirmed the on-going transformation of their
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organizations. CLO 1 reported that their organization was transforming, and that the organization
was, “no longer a ‘bank’ but a ‘tech company’.” CLO 4 noted a change in leadership was the
perturbation that promoted a transformation from a traditional organization into a more
collaborative and innovative entity. CLO 2 mentioned that their organization was going to hire a
head of transformation to prepare the organization for advancing technologies. CLO 3 stated:
We are in the age of acceleration. Our ability to innovate, our ability to evolve to mature,
iterate is really how we support our customers effectively and as a result of that this
notion, of not just lifelong learning, but continuous improvement built into our DNA. If
we are doing it the same way this year as last year, we have to look at what’s wrong as
customer preferences are driven by Amazon, Zappos, Apple, and not our traditional
competitors. Must continuously improve and ask what are the changes we need to make
to be a more customer centric organization
Most of the organizations in the study were taking steps to transform. However, the CLO
of the organization that used the word “transformation” the most in its documents (website,
annual report and online content) believed there was a disconnection between the words of the
organization and the actions of the organization. Based on Schein’s three levels of organizational
culture (artifacts, espoused values, and basic underlying assumptions), this particular
organization had artifacts and espoused values on transformation and learning, but the CLO’s
perception was that the organization was not a safe place to learn, nor was the organization
transforming. For organizations to truly be learning organizations, the organization must not only
promote learning on their websites, but begin to transform the workplace.
CLOs want to enable individuals to learn, but their organizations are not always a
safe place to learn. As reviewed in the organizational influences section, a psychologically safe
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organizational culture is vital for employees to exhibit learning behaviors. Team psychological
safety, a shared belief that it is safe to take risks in the group, is associated with learning
behavior (Edmonson, 1999). The concept of psychological safety was explored in interviews
with the CLOs, and the research found pockets of psychologically safe environments within the
studied organizations.
CLO 4 stated her team culture, admittedly, “a micro culture,” allowed her to experiment
and collaborate, whereas they saw other teams as rigid. The CLO explained, “some teams are
safe and some are not. It is baptism by fire and some groups embrace change and some
traditional units take a while longer.” CLO 6 commented that their the organization was, “nice
on the surface, but because it’s filled with so many smart people, I’m not sure how
psychologically safe it is. People need to be on guard.” CLO 5 was clear that her organization
was not psychologically safe, “It is not a safe place to learn, or challenge or take risks or to fail.
You are rewarded at the top for saying something bold and audacious and at the bottom for doing
what’s always been done.” For organizations to be successful in preparing their workforce for
the future of work, they must have, or create, organizational cultures of psychological safety.
While some CLOs have found some pockets or micro-cultures of psychological safety, not all of
the CLOs believe their organizations are safe places to take risks and learn.
CLOs may be given the role and the responsibility, but are not always given
resources. It was assumed that organizations need to provide their CLO with resources (i.e.,
budgets) so the CLO can plan and create professional development offerings on how to work
with advanced technologies. The interview data suggested that while organizations give a
commitment to organizational learning, not all heads of learning are given resources (specifically
mentioned by the CLO’s funding) despite their established roles and responsibilities within the
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organization. The organizational setting in which the head of learning resided and whether the
CLO role or learning function is given or must gather resources, can be influenced if the learning
function was centralized (one group for learning) or decentralized (heads of learning within
business units).
For CLO 1 and CLO 6, learning is centralized in their organization and have dedicated
budgets. CLO 6 added that “any function can also create a line item to dedicate towards
education as well.” While CLO 5’s organizationally resided in a centralized unit, the CLO must
secure funding from other business units which can be difficult, “I have found that internal
business units often don’t have the political clout to secure the budget or they may have the
budget, but don’t have the clout to enforce the learning.” The majority of centralized learning
functions were given funds, and another needed to secure funds from other business units, other
CLOs felt they had the funding they needed.
Fortunately, some CLOs worked in environments that allocated resources for learning
when needed. CLO 7 served a business unit which was the profit center for the organization,
“I’m fortunate. I support the profit center and we get what we need [resources].” CLO 7 also
noted the buy-in from executive leadership was important, “Our CEO sees learning as a
competitive advantage.” CLO 4 also worked directly for a business unit, which enabled her to
have a lot of, “independence and accountability,” but it still lacked resources. CLO’s 2 and 3 also
served large business units in large financial services institutions and sat centralized within their
human resource functions. Organizational settings and structures, roles and responsibilities may
imply organizational commitment to learning, but that did not guarantee the resources (funding)
the organization’s CLO believed they needed to be successful to reach the stakeholder goal of
preparing their workforce for the future.
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The organizational cultural models and settings both hinder and support CLOs. While
many of the organizations had started to transform, the organizations did not all demonstrate that
the organization was a learning organizations. While there are pockets of psychological safety
within the field of large enterprises researched, not all of the CLOs in this research perceived
their organization as a psychologically safe environment. Finally, while organizations
demonstrate a commitment to learning with heads of learning in role and responsibility, many
CLO’s believed they needed additional resources to support their organization’s external
commitment to the future of work. The large enterprises in this research know advancing
technologies will impact the workplace and the workforce, some organizations must continue
and others must begin to adapt.
Finding 4: CLOs Posit that as Technology Continues to Advance, Organizations Need to
Adapt
Organizations and individuals need to continue to, or begin, to embrace constant change.
Organizationally, this means adopting a culture of organizational learning and psychological
safety. Individually, this means adopting a growth mindset, adaptability, and agility. Promising
practices are noted in the detailed findings section of this report and additional recommendations
follow in the recommendations section.
CLOs’ leadership and development strategy is influenced by the external
environment, organizational leadership and the workforce itself. CLOs identified influencers
of their leadership and development strategies and included the external environment, the
leadership and management of the organization and the workforce themselves. They indicated
that a trifecta of influences from the outside in (external influences), top-down (leadership and
management), and bottom-up (the workforce) influences the organization, leadership and
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development strategy. The Burke-Litwin (1992) model, as noted in the conceptual framework,
argued that the external environment, organizational leadership, and individuals can influence
organizational strategies. While the research questions focused on how the organizational model
and setting influenced the organization’s CLO, it is important to highlight the bi-directional
nature that the CLO and external environment also influenced the organization. A CLO and their
leadership and development strategy is influenced by external trends, literature, their
organization’s business strategy, business units, and individuals within their organization.
Document analysis and interviews support the claim that the external environment influenced the
organization and individuals and the organization have a bi-directional relationship.
Advancing technologies are impacting organization’s missions, strategies, leadership, and
culture. The topic of advancing technologies is well documented for most of the organizations
studied. Advancing technologies are being discussed externally and many organizations are have
taken steps to transform. CLO 7 contends, “We start with our learning strategy based on the
business strategy, so if we don’t accomplish it, we haven’t done our job. We translate the
business objectives into behaviors.” CLO 1 echoed a similar statement, “the customer is the
catalyst, our CEO made the determination for the direction four or five years ago, where we are
going and it’s going to happen. It’s been an evolution.” The top-down approach from the CEO
led that organization to look at its organizational values and cultural norms, and determined the
behaviors and skill sets needed in the future. The business strategy influenced the leadership and
development strategy, and individuals within the organization also influenced the strategy
demonstrating the bi-directional relationship between the individual and the organization.
Customer centricity is a value and an influencer of large enterprise strategy because it
impacts the bottom-line. The customer is a key external influencer for organizations. For one
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organization, a customer-centric mindset is embraced for employees as well. CLO 1 also
discussed how customer-centricity is an employee-centric approach, “I serve our customers
(employees) so they can serve our end customers. On the hierarchy, the external customer is king
and we work our way backwards.” CLO 3 reported that their organizational leadership and
development strategy is also influenced by the organization’s customer preferences.
Moreover, the external environment influenced the leadership and development strategy
from the bottom-up. As featured in the Burke-Litwin model (1992), the external environment
influenced organizational strategy, and also influenced individuals and individual needs, values,
motivation and capabilities. CLO 4 noted,
There are a lot of people that want to learn and if not here, then elsewhere. The entire
digital market is looking across the globe and hence reskilling is a little more defined.
Reskilling is a driver by the employee base, not just the technology advancements. There
are changing trends in the technology market and if you can’t reskill here, they [our
workforce] would go get skills elsewhere.
CLOs noted there is a war for talent and the CLO hoped to develop employees to be
more flexible than functional. Technological, demographic and socio-economic changes had
the World Economic Forum (2016) call for, “targeted action to build a workforce with
futureproof skills” (p. 11). Given the change accelerated by advancing technologies, many
CLOs revealed that they were actively seeking talent that have the personality, mindset, or
developed skill sets of agility to help their companies transform. In addition to supporting the
finding that CLOs have the procedural knowledge and know what skill sets they need within the
organization for the future, the CLOs also note these skill sets are a change for individuals and
for organizational strategy. Several CLOs noted the, “war for talent.” A financial service
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organization’s CLO stated, “we understand that this is a talent race.” The CLO continued, “we
have more technologists than Apple Computer …. The complexion of our workforce and life is
changing significantly and being reset in a way that puts a significant premium on high-skilled
talent and a discount on mid-skilled talent.” A technology service organization’s CLO had a
similar sentiment, “we are at the place where every company is becoming a tech company, and
everyone wants same type of talent.”
The skills and behaviors being sought or developed in this war for talent included self-
awareness, creativity, and design thinking. As reviewed in finding 1, CLOs have the knowledge
and have created leadership and development strategies focused on developing their people as
people. These strategies discussed the development of skill sets in terms of mindsets and
behaviors. For CLO 1, the first part of their organization’s transformational leadership
development strategy focused on self-awareness, “we want to know you as an individual and
want you to know who you are, what motivates you? We then note, here’s what we (the
organization) needs, and then look at your goals, and the organizations goals and see if there’s a
match.” CLO 1 noted during the self-awareness component that if there was not alignment
between the individual’s goals and the organization’s goals that “It’s ok. We see attrition as a
sign of success of our leadership and development program. We want the right people in the
right jobs and if it’s not, we’ll help you find something else.” CLO 5 is looking for lifelong
learners and life skills:
Getting ready for that concept (lifelong learning) is an important thing for us to do. You
need foundational numeracy, financial literacy, foundational scientific literacy, and then
as part of that the most foundational part is your fundamental human skills: your critical
thinking, problem solving, creativity, empathy, cross cultural awareness, communication,
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leadership, resilience; your capacity to learn and change. The most important thing as a
human and then layer on top of that your capacity to be curious about changing
technology.
CLO 6 was looking for the right personality and behaviors including learning agility,
flexibility, and openness. CLO 6 stated the importance of self-awareness and helped the
organization’s leaders, “show up differently.” CLO 6’s leadership and development strategy
offers coaching, and sought to create, “spaces where managers and leaders are getting reflection
and where that reflection builds awareness and capacity.” Similarly, CLO 2 stated, “we are
starting to think about changing natures of roles of what will be automated (by technology) and
are experimenting around building, in addition to skill sets around digital literacy, life skills
around 4 c’s: courage, care, can do and curiosity.”
As organizations begin to adopt advancing technologies, their CLOs are augmenting the
skill sets of their employees. While A.I. is still in development and the immediate tasks of what
will be automated in organizations is still to be determined, CLOs are aware of the advancing
technologies and are developing their employees to be more self-aware and adaptable.
Summary of Key Findings
Research question 1. What is the CLOs’ knowledge and motivation related to creating a
leadership and development strategy to develop their workforce, considering their organizations’
adoption of advanced technologies including A.I.?
Finding 1: CLOs report to have knowledgeable about the future of work. Interviews
with CLOs demonstrated that they are knowledgeable about the impact of advanced technologies
on their workplace and their workforce. Given that A.I. is still in development, at least for the
large enterprises in this study, vast automation has not occurred. While widespread impact of
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advanced technologies has not completely disrupted the large enterprises studied, the CLOs were
knowledgeable and focused on developing their workforce for adaptability.
Finding 2: CLOs report to be motivated to prepare their workforce for the future.
Interview findings demonstrated that CLOs are motivated to prepare their workforce for the
impact of advanced technologies. CLOs expressed positive emotions around advanced
technologies. CLOs also felt confident in their ability to prepare their workforce for the future.
Research Question 2: How does the organizational culture and context support or hinder
CLO knowledge and motivation?
Finding 3: Organizational cultural models and organizational cultural settings impact
the CLOs’ ability to reach their goals. While all the organizational documents (websites)
espoused support for learning, only a few organizations were learning organizations based on the
CLO’s perception as to whether the organization was transforming. In addition, interviews noted
that some CLOs believed their organization lacked psychological safety. Finally, some CLOs
believed they lacked the resources necessary to prepare their workforce for the future.
Recommendations for Practice
From data analysis, to findings, to recommendations, this section provides a review of the
knowledge, motivation, and organizational needs assumed and identified among the CLOs
through careful review of the data collected and provides context specific recommendations to
address those needs. As the findings revealed, CLOs are knowledgeable and motivated
surrounding the topic of advancing technologies, organizational cultures both support and hinder
the organization’s workforce. Some CLOs and their respective organization have promising
practices that should be continued and adopted by other organizations as technology continues to
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advance. The knowledge, motivational and organizational influences needed now and assumed
to be needed in the future are listed in Table 6.
Table 6
Summary of Knowledge, Motivational and Organizational Influences and
Recommendations
Influences Principle and Citation Context-Specific
Recommendation
Knowledge
As their organizations begin
to adopt artificial intelligence,
CLOs need to define A.I. and
understand what advanced
technologies are adopted
within their organizations.
Managing intrinsic load by
segmenting complex material
into simpler parts and pre-
training, among other
strategies, enables learning to
be enhanced (Kirshner,
Kirshner, & Paas, 2006).
Learning is enhanced when
the learner’s working
memory capacity is not
overloaded (Kirshner et al.,
2006).
CLOs need to be provided
with information that breaks
down the complexities of new
technologies into manageable
parts.
CLOs need to know what
tasks will be completed by
artificial intelligence to
understand what tasks will be
completed by employees as
their organizations adopt
advance technologies.
Information learned
meaningfully and connected
with prior knowledge is
stored more quickly and
remembered more accurately
because it is elaborated with
prior learning (Schraw &
McCrudden, 2006).
CLOs need to be provided
with information to connect
new knowledge around
advanced technologies and
how it will change their
workforce’s work.
CLOs need to help their
workforce identify what tasks
they will do and what tasks
the technology will do.
CLOs need metacognitive
awareness and know what
they know about artificial
intelligence, understand what
they need to know about A.I.,
and how they can help
develop their workforce to
work with A.I.
The use of metacognitive
strategies facilitates learning
(Baker, 2006).
CLOs will metacognitive
awareness so that they will
know about advanced
technologies, what they do
not know about advanced
technologies, and what they
need to know to make a plan
to gain that knowledge.
Motivation
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CLOs should have positive
activating emotions around
the future of work.
Emotions affect effort,
motivation to persist, and
strategies for learning and
cognitive concepts (Pekrun,
2011).
Provide opportunities for
their workforce to discuss
their emotions about A.I.
CLOs need to believe they
and their organizations are
capable working with
advanced technologies.
Self-efficacy is the self-
perception an individual has
about their capability to
perform a specific task
(Pajares, 2006).
Collective efficacy is the
feelings an individual has
about the group’s ability to be
successful (Bandura, 2000).
Make it clear the workforce is
capable of learning what they
need to know to be successful
in the future.
Organizational
Organizations need to create
a culture of psychological
safety for employees to learn
new ways of working.
Organizations need cultural
models of psychological
safety (Edmonson, 1999).
Leaders need to model
psychologically safe
behaviors.
Organizations need to create
a culture that values
organizational learning.
Organizational culture is
created through shared
experience, shared learning
and stability of membership.
It is something that has been
learned. It cannot be imposed
(Schein, 2004).
Organizations need to
identify as a learning
organization (Senge, 1990).
Leaders should exhibit learning
behaviors.
Organizations need to provide
CLOs with resources (i.e.,
budgets) so they can plan and
create leadership and
development offerings on
how to work with advanced
technologies.
Effective accountability
systems must ensure that
adequate fiscal resources are
in place to meet
organizational goals or drive
improvement (Clark & Estes,
2008).
CLOs should be given
authority and budgets for
learning how to work with
advanced technologies.
Knowledge Recommendations
The data revealed CLOs report they are knowledgeable about the topic of advanced
technologies and the future of work, as technology continues to advance, CLO’s acquisition and
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transfer of knowledge must continue. CLOs need a range of knowledge, including conceptual,
procedural, and metacognitive, as technology continues to advance.
Increasing declarative knowledge about advanced technologies. Interview data
demonstrated that the CLOs report to possess this type of knowledge today, and as technology
continues to advance, CLOs will need this knowledge in the future. Rueda (2011) defined the
different types of knowledge from factual to metacognitive. Factual knowledge are the
definitions, terms, details, and contexts used. Conceptual knowledge are the categories,
generalizations, and classifications identified. Together, factual and conceptual knowledge are
combined to create declarative knowledge. As technology advances and organizations begin to
adopt artificial intelligence, CLOs need to be able to define what A.I. or advanced technologies
are being employed within their organizations. A.I. and advanced technologies can be perceived
as complex by some. Therefore, it will be important for the organization’s CLO to manage their
intrinsic loads.
In order to develop declarative knowledge about advancing technologies and be mindful
of the intrinsic load, principles based on managing intrinsic load should be implemented.
Specifically, Kirshner, Kirshner, and Paas (2006) found that learning can be enhanced to manage
the intrinsic load by breaking complex material into smaller parts. This would suggest breaking
A.I. and advanced technologies into learning elements would help learners. A recommendation is
to provide CLOs with informational materials about A.I. and advanced technologies including
factual information (terms, facts, and details) and conceptual information (theories, models, and
classifications), synthesized into simple and manageable pieces of information to their
workforce.
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While A.I. is difficult to define as it has yet to be completely developed, each CLO will
need to define what A.I. and other advanced technologies are and have been adopted in their
organization. To enable this knowledge, CLOs need to collaborate with and gain information on
what technologies have been employed and what the technology will do. For CLOs, materials on
what questions to ask their head of technology to clearly define what advanced technologies the
organization is employing (terms, facts and details) would be useful. To enable CLOs to have
those discussions, materials should be made available on the detailed workings of advanced
technologies, the benefits, the risks, and the tasks of technology. This detailed knowledge can
then be provided from the CLOs to their workforce for the workforce to gain knowledge about
advanced technology adoption within the organization.
Increasing procedural knowledge on how to work with advanced technologies.
Building on the declarative knowledge solutions, CLOs need to continue to have procedural
knowledge. The CLOs studied demonstrated procedural knowledge in detailing out the skills
that the CLO was developing within the organization, with specific mentions of core life skills
including adaptability. Adaptability will be key as the adoption of technology continues to
change the workplace, the workforce will need to change as well. As work changes, CLOs need
to connect the new ways of working with the old ways of working. In order to develop
procedural knowledge about advanced technologies learning strategies can be applied. Indeed,
information learned meaningfully and connected with prior knowledge is stored more quickly
and remembered more accurately because it is elaborated with prior learning (Schraw &
McCrudden, 2006). It is recommended that CLOs continue to develop adaptability as a key skill
in working with advancing technologies.
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Reinforcing opportunities to engage in metacognitive reflection. CLOs in this study
discussed awareness about their knowledge related to the impact of advanced technologies on the
workforce and the workplace. Metacognitive knowledge is knowing when to do something and
why to do it (Rueda, 2011). While CLOs in this study had metacognitive knowledge about
advanced technology, CLOs will need to continue to engage in metacognitive reflection as
technology continues to advance. As artificial intelligence advances, CLOs need to understand
what they need to know about artificial intelligence, and how they can continue to grow and
develop and work with A.I. in their organization. To develop metacognitive knowledge, CLOs
need strategies. Specifically, as Baker (2006) contended, metacognitive strategies help facilitate
learning. It is recommended that CLOs continue to identify what they know about advanced
technologies, what they do not know about advanced technologies and what they need to know,
and plan to develop that knowledge to be successful in the future.
Metacognitive awareness is a form of knowledge, a way to acquire that knowledge is by
becoming a reflective practitioner. A reflective practitioner is one who incorporates double-loop
learning (Schon, 2017). Single loop learning is a process where the individual looks to improving
efficiency by obtaining the established objectives or, “doing things right,” double-loop learning
changes the objective and questions the assumptions about that objective (Argyris & Schon,
1974).
When considering new ways of working, a CLO and their workforce need to reflect on
their own process of learning and generate metacognition around what they know and need to
know around advanced technologies. Metacognition is a process and metacognitive knowledge is
a product and reflection, “provides the critical link” between knowledge and control of the
process (Ertmer & Newby, 2004, p. 3). Some of the CLOs noted their development of their
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employees’ self-awareness and self-reflective practices. Those organizations should continue
those initiatives, while other organizations should seek to develop a reflective practice within the
organization. A reflective practice is one where the learner becomes aware of their implicit
knowledge base and learn from their experience (Schon, 1987). It is through a reflective practice
that learners may also discover what they need to know to be successful in the future and
develop learning strategies of how to gather that knowledge.
Motivational Recommendations
The data revealed CLOs are motivated to prepare their workforce for the future. This
study found CLOs have both activating positive emotions and self-efficacy around the topic of
advanced technologies and the future of work. As technology continues to evolve, CLOs must
maintain their motivation and help foster collective-efficacy within their organizations.
Maintaining positive affect about advancing technologies. Interviews with the CLOs
illustrated their positive feelings about artificial intelligence. As motivational principles suggest,
emotions positive or negative, activating and deactivating, affect effort, motivation to persist, and
strategies for learning and cognitive concepts (Pekrun, 2011). Based on this academic literature,
it is recommended CLOs need to use their metacognitive awareness to self-regulate their
emotions, and foster positive feelings within their workforce about the topic of artificial
intelligence. CLOs need to be excited about working with advanced technologies to gain the
knowledge needed to be a valued employee in the Fourth Industrial Revolution. Therefore, it is
recommended that there are opportunities for CLOs, and their workforce, to discuss their
emotions around advanced technologies.
Indeed, A.I. can elicit a range of emotions even amongst experts. Depending on if A.I. is
considered an opportunity or a threat, A.I. could elicit positive activating emotions of hope,
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pride, and enjoyment, or negative deactivating emotions of hopelessness. CLOs need to ensure
that they and their workforces remain positive and persistent in learning how to work with
machines and augment their skill sets. While the CLOs studied have not expressed negative
emotions, they need to be mindful of their own and their employees’ feelings about the topic.
Employees that experience deactivating emotions may find it difficult to develop the knowledge
needed to be successful in the future.
Reinforcing CLO beliefs that they can prepare their workforce for the future. The
CLOs interviewed revealed they had self-efficacy, which will help them persist and regulate their
own actions and cognitions around advanced technologies. Positive self-efficacy impacts
(academic) performance; therefore, to increase performance, it is recommended to encourage
leaders to both equip and allow employees to apply self-leadership strategies to specific work
activities (Prussia, Anderson, & Manz, 1998). Utilizing these recommendations, the
organization’s employees’ confidence and performance could be enhanced.
Developing collective-efficacy. While the CLOs studied had self-efficacy, some of the
CLOs questioned the collective-efficacy. Collective-efficacy is the feelings an individual has
about the group’s ability to be successful (Bandura, 2000). Collective-efficacy will be important
for CLOs to have and to foster in their workplace. Based on collective-efficacy principles, it is
recommended, that it be made clear that CLOs and the organization’s workforce are capable of
being successful in working with advanced technologies in the future.
Positive collective-efficacy impacts (academic) performance (Goddard, Hoy & Woolfork
Hoy, 2000). Therefore, to increase performance, leaders should create opportunities for
collaboration, gain knowledge, interpret performance results while providing feedback with a
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vision for success, and involve the workforce in decision making. Those actions have helped
schools evolve into schools with strong collective efficacy and improve learner performance.
Organizational Recommendations
The data revealed the organizational cultural models and settings impact the CLOs as did
the external forces. As Lewin stated, “behavior is a function of a person in his or her
environment” (1936, p. 4). Organizational culture, and how the organization works, impacts how
a manager leads and influences employee behaviors (Burke & Litwin, 1992). The organizational
cultural model emphasized that culture is both what people say about the organization and how
people work in the organization (Schein, 2004). Schein (2004) synthesized organizational culture
into three levels: 1) artifacts (the visual organizational structures and processes), 2) espoused
values (strategies, goals, philosophies), and 3) basic underlying assumptions (unconscious, taken
for granted beliefs, perceptions, thoughts and feelings, ultimate source of values and action).
Gallimore and Goldenberg (2001) defined culture as cultural models and cultural settings.
Cultural models are often invisible and unnoticed. Cultural settings include the location and
occasion where people come together to carry out joint activity that accomplishes something
they value. Organizational cultures need to be open and collaborative while reskilling the
workforce (MGI, 2017). Organizations will need cultural models of psychological safety and
identify as a learning organization (Edmonson, 1999; Senge, 1990).
CLOs need to help create an organization that is a psychologically safe environment and
a learning organization. CLOs must have the resources they need to develop the organization’s
workforce for the future. This study found that some CLOs did not believe their organization was
a psychologically safe environment and the organization was not a learning organization. As
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organizations begin to adopt new technologies, the organizational culture (model and setting)
will need to adapt as they adopt.
Creating a culture of psychological safety. The data analysis revealed some CLOs
believed their organizations were not psychologically safe environments. Organizations need to
create a culture of psychological safety for employees to learn new ways of working.
The concept of team psychological safety is a shared belief by team members that it is safe to
take risks in the group (Edmonson, 1999). Therefore, it is recommended based on the principles
of psychological safety, that CLOs create a safe environment by being accepting of ideas,
encouraging all questions, eliminating judgment, encouraging wild ideas, and give and receive
feedback in a way that makes the individual, the organization, and the ideas better.
Psychological safety described an environment where employees have interpersonal trust,
mutual respect, and are, “comfortable being themselves” (Edmonson, 1999, p. 2). Psychological
safety has a positive influence on organizational learning and performance. Edmonson’s research
demonstrated team psychological safety is associated with learning behavior. For employees to
learn a new way of working, the organizational culture must be one of psychological safety. A
psychologically safe organizational culture is vital for employees to exhibit learning behaviors,
and psychological safety must be present before teams can learn and innovate.
Transforming into learning organizations. The data revealed many of the
organizations studied promote learning, but the organization’s CLO believed their organization
was not a learning organization. Organizations need to create a culture that values organizational
learning. Organizational culture is created through shared experience, shared learning, and
stability of membership and is something that has been learned and cannot be imposed (Schein,
2004). Organizations need to identify as learning organizations (Senge, 1990). Based on the
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principles of organizational learning, it is recommended that leaders model learning behaviors.
Learning behaviors include acknowledging one’s mistakes, being approachable and encouraging
people to ask questions, listening actively, encouraging people to share more and ask more
questions, and continuing to learn by taking and attending courses and acquiring knowledge.
A learning organization promotes learning and is continuously transforming (Senge,
1990). A culture of organizational learning occurs when employees can expand their capability,
new patterns of thinking are encouraged, and people are continually learning how to learn
together (Senge, 1990). Beyond a learning organization in theory, Kiedrowski (2006) studied the
impact of learning organization concepts on job satisfaction and found employee satisfaction
increased with the acceptance of learning organization concepts. Thus, becoming a learning
organization will be necessary because of the rapidly changing external environment, and
because it is worth investing in for the competitive advantage of employee satisfaction.
Availing dedicated resources to prepare workforce and workplace for the
future. The findings suggest many CLOs need more dedicated resources to prepare their
organization for the future. Organizations need to provide their CLO with resources, specifically
funding, so the CLO can plan and create professional development offerings on how to work
with advanced technologies. Effective accountability systems must ensure that adequate fiscal
resources are in place to meet organizational goals or drive improvement (Clark & Estes, 2008).
It is recommended that the organization’s CLO be given the resources they need to specifically
develop professional offerings on how to work with advanced technologies. CLOs should
develop a specific plan and budget for learning how to work with advanced technologies. For
CLOs, the task of developing new skills is something that will require new knowledge and
motivation, but also resources, such as budgeting and staffing, from the organization.
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Integrated Implementation and Transformational Program for CLOs
Implementation and Evaluation Framework
Kirkpatrick (2013) recommended leaders start with understanding and determining the
business needs and opportunities (level 4 results), define non-negotiable required behaviors
(level 3 behavior), identify required knowledge, skills, and attitudes for the required behavior
(level 2 learning) and determine learning environment that will facilitate obtaining required
knowledge and skills (level 1 reaction). While all of Kirkpatrick’s levels are important, this
researcher argues that the levels are not linear. Level 1 of Kirkpatrick’s model discussed the
organizational culture or learning environment which is key to an organization's success.
Kirkpatrick’s level 4 (results) revealed which business needs and opportunities make the case for
change and define learning and motivation. While Kirkpatrick and Kirkpatrick (2016) noted that
if Levels 1 through 3 (reaction, learning, behavior) are done well, there will be results, Level 4
still needs to be determined prior to developing a plan with an understanding of the culture.
While Kirkpatrick’s intentions are useful, the focus on training is more pedagogical than
andragogical. Knowles’ defined pedagogy as the transmittal of knowledge and skills (Knowles,
1980). A pedagogical model is one that transmits information and skills which are determined in
advance by the leader, the content is arranged into logical units, the most efficient means for
transmitting this content is selected, and then a plan is developed for presenting these units in
some sequence (Holmes & Abington-Cooper, 2000). However, adult learners seem to, “feel this
was insufficient and frequently resisted teaching strategies that pedagogy prescribes, such as
lectures, assigned readings, drills, quizzes, note memorizing, and examination” (Holmes &
Abington-Cooper, 2000, p. 51) The goal of adult learning (andragogy) is self-actualization
(Knowles, 1980). For adult learners, the learning process should involve the whole emotional,
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psychological, and intellectual being (Knowles, 1980). While Kirkpatrick’s work aligned with a
pedagogical model, this researcher recommends taking an andragogical approach. In an
andragogical approach, the process is concerned with providing procedures and resources for
helping learners acquire information and skills through a leader, a facilitator, change-agent, or
consultant. The andragogical model prepares a set of procedures for involving the learners in the
process by 1) Establishing a climate conductive to learning, 2) creating a mechanism for mutual
planning, 3) diagnosing the needs of learning, 4) formulating program objectives that will satisfy
these needs, 5) designing a pattern of learning experiences, and 6) conducting these learning
outcomes and diagnosing learning needs (Holmes & Abington-Cooper, 2000)
The following recommendations include an integrated implementation for the workforce
and a transformational program for CLOs. The program incorporated intentions of the
Kirkpatrick model and the use of an andragogical program. The combination of these
worldviews will allow for the learner to be a part of the development of the program.
Organizational Purpose, Need, and Expectations
As technology advances, leaders need to understand the impact of these technologies on
their organizations and the skill sets that employees need in the future (WEF, 2018). As
organizations adopt new technologies, the organization needs to adapt the organizational culture
and the workforce skill sets needed for success (MGI, 2017). Therefore, the CLO’s knowledge,
motivation, and the organizational culture will impact the organization’s ability to adapt as they
adopt.
Level 4: Results and Leading Indicators
In developing their workforces for the future, CLOs need to understand their
organizations desired outcomes and develop metrics and methods. Table 7 outlines potential
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outcomes. Internal indicators are defined to monitor and measure changes within the
organization. External indicators are used to define how the external environment will respond to
successful transformation of the organization.
Table 7
Outcomes, Metrics, and Methods for External and Internal Outcomes
Outcome Metric(s) Method(s)
External Outcomes
Increased promotion
of reskilling initiatives.
The frequency and number of
external mentions (in press
releases, briefings, annual
reports, marketing and
communication materials) on
this topic.
Track the frequency and mentions
of this initiatives with the external
audience (in press releases,
briefings, annual reports,
marketing and communication
materials).
Internal Outcomes
Increased confidence
regarding the adoption
of advanced
technologies in the
workplace.
Organizational survey results on
key questions.
Compare annual or bi-annual
survey results.
Increased professional
development
opportunities on
working with
advanced
technologies.
Documentation of professional
development plan includes
offerings on working with
advanced technologies.
Audit of learning and
development plan and offerings.
Increased investment
in advanced
technologies.
Measure the budget/ resources
allocated to advanced
technologies.
Compare the annual budgets of
technology and line item for
advanced technologies.
Increased investment
in employee
development.
Measure the budget/ resources
allocated to employee
development in relation to
working with advanced
technologies.
Compare the annual budgets for
leadership and development and
line item for working with
advanced technologies.
Level 3: Behavior
Critical behaviors. Kirkpatrick’s third level examines behaviors. In Table 8,
recommended behaviors are listed which will help achieve Level 4 outcomes. In the required
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drivers section, it is worth monitoring the environment both before and after the intervention to
ensure it is supporting the transfer of learning.
Table 8
Critical Behaviors, Metrics, Methods, and Timing for Evaluation
Critical Behavior Metric(s) Method(s) Timing
Leaders are accepting and
encouraging of ideas.
Number of ideas that
employees contribute
(increase).
Observations After 90
days
Ongoing -
weekly
2. Leaders are encouraging of
questions.
Number of questions
from team members
collected by team
leaders.
Observations After 90
days
Ongoing -
weekly
3. Leaders give and receive
feedback in a way that it is
to make the individual,
organization and idea
better.
Number of interactions to
provide and receive
feedback.
3a. Survey
3b. 360 feedback of
managers
After the
initial 90
days
Bi-annually
Leaders are modeling trust
and safety.
Number of acts of
positive reinforcement by
leaders.
4a. Survey of
employees
4b. Analysis of
employee evaluations
(are employees being
penalized).
4c. 360 feedback of
managers
After the
initial 90
days
Bi-annually
Leaders are modeling
learning behaviors.
Number of professional
development activities
practiced.
5a. Observations
5b. Course attendance
After the
initial 90
days
Ongoing
Leaders are modeling
openness.
People at all levels of the
organization (believe
they) are given a voice
and genuinely heard.
6a. Observation
6b. Survey of
employees
After the
initial 90
days
Ongoing
Required drivers. Required drivers support these critical behaviors, including the
development of an organizational culture of psychological safety. The environment must evolve
both before and after the intervention as the environment will not support the transfer of learning
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or support the behavior change if it is not one in which it is safe for the participant to learn or
work differently.
Table 9
Required Drivers to Support Critical Behaviors
Method(s) Timing
Critical
Behaviors
Supported
1, 2, 3 Etc.
Reinforcing
Leadership and development offerings in the form of courses,
coaching, blog posts, recommended reading, etc. are provided.
Monthly All
Team meetings include open communication, dialogue,
discussion and shared learnings.
Weekly All
Ongoing feedback and communication. Ongoing All
Job aids on how to work with machines. Bi-
Annually
5
Encouraging
Leaders are modeling learning behaviors and learning transfer
which is encouraging to employees.
Daily All
Collaboration and peer modeling during team meetings Weekly All
Feedback and coaching from team lead. Monthly All
Rewarding
All Company (all hands meetings, offsites, etc.) events and
internal communication (newsletters, emails, etc.) mention
organizational learning.
bi-
annually
All
Monitoring
Employee surveys asking for participants to report confidence,
self-efficacy and psychological safety.
Bi-
annually
All
All employees (regardless of level) can assess learning,
performance, and safety through 360 feedback, and help the
organization monitor progress and make adjustments.
Bi-
annually
All
Organizational support. Learning and the transfer of learning are critical outcomes of
human development (Ciporen, 2010). The transfer of learning is complex and involves multiple
factors and influences (Holton, Bates, & Ruona, 2000). The transfer of learning is the
application, generalizability, and maintenance of new knowledge and skills (Ford & Weissbein,
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1997). Kirkpatrick (2013) suggested that learning transfer is achieved if one sees a change in
behavior. However, transfer of learning can be affected by several influences including, trainee
characteristics (ability, personality and motivation), training design (strong transfer design and
appropriate content), and the work environment (support and opportunity to use) (Baldwin &
Ford, 1988). Mathieu, Tannenbaum, and Salas (1992) suggested that while learning may occur in
training, the transfer (work) climate may support or inhibit application of learning (or behavior
change) on the job.
Perhaps, non-coincidentally, for CLOs to create an environment of psychological safety,
the CLO needs to feel they are in a psychologically safe environment. The business aphorism
coined by Drucker (date unknown), “culture eats strategy for breakfast” extends here to
organizational learning. The organizational leadership and development strategy will only be
successful if the organization’s culture supports learning. While that seems both obvious, many
organizations promote and provide learning opportunities, but the organization does not create
the space or the opportunities for the learners to apply their new knowledge.
Level 2: Learning
Learning goals. Learning can be defined in different ways. In Kirkpatrick’s Level 2,
learning is evaluated if the intended knowledge and motivational information provided in the
intervention was acquired. As organizations adopt advanced technologies and CLOs prepare
their workplace and the workforce for the future, the organization’s CLO will need to be able to:
1. Define A.I. and provide details of what advanced technologies are being employed within
their organizations. (Declarative knowledge)
2. Define what tasks will be completed by A.I. and determine what tasks will be completed
by employees. (Procedural knowledge)
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3. Determine what (new) skill sets employees need (complex problem solving, critical
thinking, cognitive flexibility, mathematical reasoning and active learning) to be
successful in the workplace. (Declarative/ Procedural knowledge)
4. Plan a leadership and development strategy to develop employees to work with advanced
technologies. (Declarative/ Procedural knowledge)
5. Support their workforce in developing self-learning strategies to learn about A.I. and
work with advanced technologies. (Metacognitive/ Procedural knowledge)
6. Indicate confidence that they and their organizations are capable of effectively
developing a leadership and development strategy to work with advanced technologies.
(Self-Efficacy/ Collective-Efficacy)
7. Define and create a culture of psychological safety to allow for individual and
organizational learning. (Cultural Model/ Psychological Safety)
8. Create a culture that values learning. (Cultural Model/ Organizational Learning)
Just like there are many definitions of learning, there are also several ways in which
learning occurs. Mezirow (2000) identified four ways of learning: 1) by elaborating existing
frames of reference, by learning new frames of reference, 3) by transforming points of view, or
4) by transforming habits of mind. The aforementioned learning goals are what Kitchener (1983)
described as the first level of cognitive processing in which individuals compute, memorize,
read, and comprehend. Some of the listed learning goals target second level cognitive processing,
which is metacognitive in nature. Kitchener’s third level of cognitive processing is
transformative, and is where epistemic cognition occurs in adults. Epistemic cognition occurs
when individuals reflect upon the limits and certainty of their knowledge and criteria of
knowing. Epistemic knowledge influences how individuals understand the nature of problems
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and determine what kinds of strategies are appropriate for solving them (Kitchener, 1983). The
program recommended aims to address the learning goals of the first and second levels of
cognition.
Program. Illeris (2002) defined learning as, “all processes that lead to relatively lasting
changes of capacity whether it be of a motor, cognitive, emotional, motivational, attitudinal or
social character” (p. 17). The future of work and impact of advanced technologies will transform
both workplaces and workforces. Learning must be inherently transformative.
Transformative learning is defined as, “learning that transforms problematic frames of
reference to make them more inclusive, discriminating, reflective, open, and emotionally able to
change” (Mezirow, 2003, p. 58). A core concepts of transformative learning theory is making
meaning as a learning process. For adults, learning is emphasized by contextual understanding,
critical reflection on assumptions, and validating meaning by accessioning reasons (Mezirow,
2000, p. 3).
A transformative learning program within the CLO’s workplace for their workforce
needs to be developed. CLOs would also benefit from attending a transformative learning
program on the future of work for chief learning officers of large enterprises. The external
program should include participating in a community of both learners (CLOs), knowers (experts
in the topic of A.I. and advanced technologies), and transformational learning facilitators.
Mezirow (2000) indicated that transformative learning begins with a disorienting dilemma.
For this community, the disorienting dilemma is the future of work and impact of
artificial intelligence. The program should allow community members to explore their feelings,
assumptions, and the process of transformation is shared. Participants should be able to explore
options for new roles, relationships and actions, plan a course of action, acquire knowledge and
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skills for implementing one’s plans. The program should build competence and self confidence
in new roles and relationships and reintegrate into one’s life on the basis of conditions dictated
by one’s new perspective as recommended by Mezirow (2000).
Evaluation of the components of learning. It is important to evaluate the declarative
and procedural knowledge being provided and seek to understand if that knowledge is being
consumed. For learners to be successful in solving problems, they need to be able to acquire and
apply declarative and procedural knowledge. Learners must also be confident in that acquisition
and application. Table 10 lists the methods and timing for evaluating these components of
learning.
Table 10
Evaluation of the Components of Learning for the Program
Method(s) or Activity(ies) Timing
Declarative Knowledge “I know it.”
Knowledge check through discussions “pair, think, share” and other
individual/group activities
Quarterly during
program meetings
Procedural Skills “I can do it right now.”
Demonstration in groups Quarterly during
program meetings
Quality of the feedback from peers during group sharing Quarterly during
program meetings
Individual application of skills Ongoing
Retrospective post program meeting discussions Following program
meetings
Attitude “I believe this is worthwhile.”
Communities observation of participants statements and actions
demonstrated that they see they believe they and their organizations
would be successful
Ongoing/ Quarterly
during program
meetings
Group discussions on beliefs/ feelings around the future of work Ongoing/ Quarterly
during program
meetings
Confidence “I think I can do it on the job.”
Survey items using scaled items Following the program
meetings
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Community discussions Ongoing/ Quarterly
during program
meetings
Commitment “I will do it on the job.”
Discussions following practice and feedback Following the quarterly
program meetings
Create an individual and organizational action plan During and following
the program meetings
Retrospective assessment Following quarterly
program meetings
Level 1: Reaction
To measure the reactions of the targeted learners, evaluations should be included in Level
one. Indeed, the proposed solution for the workplace will need to be piloted and iterative. The
CLOs will also need the external program to be iterative in design. The internal and external
programs should seek to incorporate feedback from participants to help ensure the content and
components are relevant and engaging. Kirkpatrick and Kirkpatrick (2016) state that evaluation
methods should be simple and inexpensive. Using tools such as surveys, observations, and pulse
checks will help achieve those goals. The program will be experiential in nature and seek to
deliver content to all learning styles to help learners both perceive and process the
information (Kolb, 1984). Table 11 includes the Level 1 reaction summative and formative
evaluation methods and timing.
Table 11
Components to Measure Reactions to the Program
Method(s) or Tool(s) Timing
Engagement
Attendance at program kickoff During program kickoff
Attendance at program events (in person) During program events (in person)
Attendance / participation during program
calls
During program conference calls/ touch bases
Facilitator observations Ongoing (during program events - in person &
conference calls)
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Participation in large groups (observation/
attendance/ participation)
During program events (in person & conference
calls - observation/ attendance/ participation)
Participation in small/ breakout groups
(observation/ attendance/ participation)
During program events (in person & conference
calls - (observation/ attendance/ participation)
Relevance
Program cohort discussions During program events
Program retrospectives Following program events
Live brief pulse check with participants During program events
Program evaluations Following program events
Customer Satisfaction
Program cohort discussions During program events
Live brief pulse check with participants During program events
Program evaluations Following program events
Evaluation Tools
Immediately following the program implementation. To analyze and evaluate the
transformational learning program, the program will collect data concerning attendance and
participation. As the program will not be mandatory, attendance is not a given. Therefore,
participants whom attend multiple or all sessions would demonstrate engagement with the
content. The facilitator should observe attendance and whether the program participants are
actively engaged.
To analyze and evaluate Level 2, participants should be asked in one-on-one
conversations to define elements of declarative and procedural knowledge such as: what
advanced technologies are being used within their organization and what organizational work
tasks would be completed by artificial intelligence. CLOs should be asked to determine what
(new) skill sets employees need in their workplace. CLOs should be asked if they have created a
leadership and development strategy to develop employees to work with advanced technologies.
CLOs should be asked if they are confident that they and their organizations are capable of
effectively developing a leadership and development strategy to work with advanced
technologies.
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Delayed for a period after the program implementation. Approximately 90 days
following the completion of the pilot program, the program facilitator should follow up with
program participants to see if the cohort learning has transferred, and if not, seek to uncover
potential organizational barriers that need to be addressed. One-on-one interviews should be used
to further discuss Level 1 reaction to the program and gain feedback for how the program can
improve. The interviews should also focus on Level 2 learning and what may need to clarified or
improved upon to deliver learning, and Level 3 transfer to understand how both the individual is
able to transfer the learning and what, if any, organizational barriers need to be addressed.
Transformational Learning Program Data Analysis and Reporting
The analysis and reporting should focus on both the participants and the program
facilitators and directors. Demonstrating double-loop learning, the facilitators should consider
the feedback and observations throughout the session and iterate the following sessions based on
the feedback and recommendations of participants. This will indicate to the participants that their
feedback is valued and utilized. The continuous feedback and observation cycle should allow for
the facilitators to improve program quality and enhance the learning experience by ensuring the
content is relevant for the participants, as well as build the participants’ confidence in applying
their learning within their own respective organizations.
Following the pilot program, evaluative data should be collected to determine and
develop an organizational case for organizational buy in. The Brinkerhoff (1983) Success Case
Method will help evaluate and improve the program throughout its implementation, as well as
identify and promote how, when, and where the learnings benefited the participants and the
organization.
Summary
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The Kirkpatrick (2013) model is helpful in setting program intentions and being mindful
of how to measure program outcomes. While the Kirkpatrick model is rooted in training, it does
not always consider the organization, the audience, or the organization’s challenge. The
Kirkpatrick model is valuable in its intention to develop and measure learning, but does have its
shortfalls. The author sees the Kirkpatrick evaluation model as more single-loop in nature
focusing on the levels to improve efficiency to obtain the established objectives. The author
would argue that in developing an adult learning transformational program that the program
incorporate double-loop learning to question the assumptions about that objective, the ways of
discovering and inventing new alternatives, objectives, and perceptions, as well as ways of
approaching problems. The Kirkpatrick model when used in combination with Mezirow’s
Transformational Learning Theory, should lead to the development and implementation of
valuable interventions for CLOs. The designed program should return on both the CLOs and
their respective organization’s expectations to address impact of advanced technologies on the
organization’s workplace and workforce.
Limitations and Delimitations
Limitations are influences outside of the researcher’s control which may restrict the
study’s methods and conclusions. Noted limitations of this research included using a network
sampling approach that relied upon professional connections to facilitate access to large
enterprise CLOs. Self-reporting is a challenge as participants could exaggerate or minimize their
feelings or beliefs and participants can be influenced by group dynamics and the organization.
While participants were assured their interviews would be anonymized, participants can answer
questions with what they believe is the ‘correct’ answer or the answer the researcher was
seeking. Merriman and Tisdell (2006) noted participant reflexivity as a limitation in qualitative
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81
research. An additional limitation was the request of all the participants to conduct the interview
over the phone. In-person interviews, within the participant’s organizational setting would have
allowed for additional observations on the organizational cultural to be collected in field notes. A
final limitation was time. While many participants agreed to an hour long interview, some had to
end the interviews early.
Deliberate choices that the researcher made to focus and set boundaries are the
delimitations of the study. The delimitations of the study include conducting qualitative research,
which is inductive rather than deductive in nature. Findings are not generalized to a specific
industry. An additional delimitation of the study is the focus of one stakeholder, the CLO, within
the large enterprise. As noted in the stakeholder group of focus section, all stakeholders
(including the Chief Executive Officer, Chief Financial Officer, Chief Technology Officer, etc.)
impact an organization’s success and are responsible for preparing the organization for the
future, however, for practical purposes, this study focused on the CLO of an organization.
Recommendations for Future Research
Advancing technologies present a number of challenges and opportunities that need
further exploration. While the recommendations address how to prepare the workforce and the
workplaces for 2020, additional research needs to be conducted both within organizations and
within society. As reviewed, historically, scholars and individuals have feared automation and
current studies suggest that new advancements in technology will again impact the future of
work. While individuals have often feared automation, organizations have embraced it.
Automation has historically contributed to productivity (MGI, 2017).
Indeed, publicly traded organizations (including the large enterprises in this study) have a
market or managed market (outward) accountability model with the goals of the provider to be
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responsive as measured by outcomes and outputs as indicators and the consequences of the
outcomes of profit and loss (Burke, 2004). Large enterprises seek to deliver results to
shareholders, but research should be conducted on at what cost to society.
The productivity paradox is the perceived discrepancy between information technology
(IT) investment and IT performance (Solow, 1987). Solow’s productivity paradox was based on
the observation that as investment in information technology increased, worker productivity
decreased. The Solow paradox was based on empirical evidence from the 70s-80s that while
technology investments were high; productivity at the macro-economic level was low. In 1994,
Brynjolfsson found four causes for Solow’s paradox: mis-measurement (there were gains, but the
measure missed them), redistribution (private gains came at the expense of other firms and
individuals leaving little net gain), time lags (the gains take a long time to show up), and mis-
management (no gains because of unusual difficulties in managing IT or information itself).
A 2018 McKinsey article described how historically during a time of restrained
productivity, what follows is a time of productivity growth enabled by technology (Krishnan,
Mischke & Remes, 2018). The article noted productivity growth was enabled by innovation in
processes, products, and services with major benefits accruing to players on its leading edge, and
to the economy as a whole. McKinsey predicted advancing technologies will yield tremendous
productivity gains with a potential productivity growth of at least two percent per year over the
next decade, with about 60%coming through digitization (MGI, 2018).
In this Fourth Industrial Revolution there is yet again, a fear that technology will replace
workers. The challenge, as in the past, is the measurement of output is difficult as is measuring
the input. The quality of inputs can vary including the quality of labor and understanding how
many employees actually are involved with IT (Macdonald, Anderson & Kimbel, 2000).
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The productivity paradox is mentioned as advanced technologies become available the
decisions to invest in technologies have impacts both at the macroeconomic and microeconomic
levels. Organizations seeking to measure and manage IT investment should acknowledge lessons
of the past. Output gains may be more than just in automation, but also though digitization, some
companies and individuals will gain more at the expense of others. The gains will take time
before they are realized and managing IT and information can be difficult.
As companies determine the job to be done (Christensen et al., 2007) companies will
determine what tasks can be completed by machine and which will be completed by people. The
job to be done will be a function of both people and technology. As companies determine the job
to be done, to meet the needs of their customers and deliver value to their shareholders, the
companies will get the job done through their investments in technology and people. Additional
research should be conducted with organizations on their investments in technology and
investments in people and how the investments are measured. A specific area of investigation
should be conducted on enterprise investment in the workforce and the workplace where in
which encouraging and allowing employees to ask more questions ‘what if’ yields a greater
return than if the organization solely invests in technology and the automation of if, then.
Additional research also needs to also be conducted at the macro level on society’s
preparation for the impact of artificial intelligence. Research should be conducted to understand
what schools are doing to prepare students for jobs in the future including developing digital
literacy, adaptability, critical thinking, creativity, emotional intelligence, judgement, and service
orientation. Research also should be conducted on what governments are doing to prepare their
communities. Finally, more research needs done on the ethics of artificial intelligence and the
impact of its automation on tasks, skills, the workforce and society. As technology continues to
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advance, more thoughts, more data, more insights, more analysis and more research needs to be
conducted.
Conclusion
The Fourth Industrial Revolution has similar fears and opportunities as past Industrial
Revolutions. As Adam Smith noted in 1776, productivity increases when labor is separated and
different tasks are given to different people. As in the First Industrial Revolution, jobs in the
Fourth Industrial Revolution, jobs will be automated by machines. While advanced technologies
will impact work, it is still to be determined exactly how. While many fear artificial intelligence,
others embrace its potential. Organizations, and individuals, that are aware of advanced
technology should be adaptable. As the world continues to change with technological
advancements and the specific tasks of what machines will do, those innate human skill sets will
be something technology will take time to master. While many experts focus on the development
of artificial intelligence, individuals should continue to develop themselves. Individuals will
need various types of knowledge to be successful in the future and will need motivation to persist
in gaining that knowledge. Individuals and organizations should invest in learning, creative
thinking, and complex problem solving. In the The Innovator’s DNA: Mastering the Five Skills
of Disruptive Innovators the authors suggest running question-storming sessions to generate as
many questions as possible to get to the right problem and the right question (2011). Machines
are good at automation, following if then statements, and activities and tasks that are routine and
anticipated can be easily automated. People can learn to ask questions. If organization’s want to
be innovative, the organization needs to create psychologically safe environments where it is not
only ok to ask questions, but questions are encouraged which will help the organization become
a learning organization and transform. For individuals the ability to ask questions, be creative
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problem solvers, do complex thinking, ask What if? Is valued in the market. Thinkers together
with machines will help companies get the job to be done, done. The ability to ask what if is
greater than routine skillsets of if then. In conclusion, the invention of artificial intelligence will
allow individuals to reinvent themselves.
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Appendix A: Interview Protocol
Interview Protocol
Draft script. Hello, let me introduce myself, my name is Carly Cooper, I am a doctoral
candidate at the University of Southern California studying organizational change leadership. I
would like to first begin with expressing my gratitude for agreeing to participate in my study.
Thank you taking some time out of your extremely busy schedule to meet with me and answer
some questions. This interview will take about an hour, although we have allocated an hour and
half for some cushion on time. I’ll be sure to mind the time as we go along.
My research is focusing on the impact of advanced technologies on the workplace.
Today, I am only here as a researcher collecting data for my study. The information you share
with me will be placed into my study as part of the data collection. In addition, this interview is
completely confidential and your name or responses will not be disclosed to anyone or anywhere
outside the scope of this study and will be known only to me specifically for this data collection.
While I may choose to utilize a direct quote from you in my study, I will not provide your name
specifically and will make the best effort possible to remove any potential identifying data
information. I will gladly provide you with a copy of my final product upon request.
During the interview, with your permission, I will use a recording device to assist me in
capturing all of your responses accurately. Following our interview, I will use software (such as
rev.com) for transcription and personally remove all identifiers. This recording will not be
shared with anyone outside the scope of this project. The recording will be transferred to my
password-protected files on a cloud file storage account and deleted from the recording device
immediately upon transfer. The recording will then be destroyed after two years from the date
my dissertation defense is approved.
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With that, do you have any questions about the study before we get started? If not, I
would like your permission to begin the interview. May I have your permission to record this
conversation?
Outline
● Introduce self (name, doctoral student studying organizational change leadership)
● Thank the participant for helping with interview
● Explain the purpose of the interview: to understand their perspective of preparing
their workforce for the future
● Explain your participation is voluntary. You can stop the interview at any time; you
can skip any question you wish.
● Explain that their responses are anonymous: you will not be naming them in your
assignment, nor will you attribute anything said to a specific person. You will not
discuss what they said, using their name or any identifiable characteristics with
anyone else.
● Permission to Record
● Press Recording
● Reiterate Permission to Record
Questions
● Background and Context
● I’ve introduced myself and my role, can you tell me a bit about your role and
responsibilities?
● How and when did you join XYZ?
● Can you tell me a bit about XYZ as an organization?
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● How did you come to be the CLO of XYZ?
● Can you tell me a bit about your leadership and development philosophy?
● Dig Deeper on Organization and Culture
● Culture and Artifacts - espoused values. In terms of your organization’s values, what
are your leaders saying? What is the organization’s purpose? Vision? Mission?
● Organizational Setting - (if onsite, note observations of artifacts (what is hanging on
the walls, room set up (cubicles?), dress codes, people in the office, gathering areas).
○ Can you describe your office? What is on the walls, floorplan (open concept,
cubicles?), front entry (if onsite, get permission to take pictures)
○ How does it feel to work here? What do you like about your company? Wish
about your company? Tell me more.
○ How does your company feel about learning? How does your company feel
about innovation?
■ How does the organization foster these values, if at all? (listen for
areas around psychological safety - safe to ask questions? Throw out
ideas? Make mistakes - ask for examples and clarifications: Tell me
more)
● Direct towards A.I.
● There is a lot of talk in the world about the impact of artificial intelligence and
advanced technologies on the workforce, what is your perspective about advanced
technologies and the future of work?
● Motivation: How do you feel about the advancement of technology? (Get into
motivation) Do you believe we are prepared (as a society) for the impact of A.I.? To
THE IMPACT OF ADVANCED TECHNOLOGIES ON THE WORKPLACE AND THE
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what degree do you believe your organization is prepared for the impact of A.I.?
(How? How not?)
● Transition – build from responses and dive more into organization and advanced
technologies.
● Knowledge: How is your organization approaching A.I., if at all? What advanced
technologies or automation are you employing in your organization, if any?
○ What tasks, if any, will A.I. do in your organization?
○ What tasks, if any, will your employees do? (Exploring the knowledge of A.I.
and the knowledge of who and what is happening in the organization)
○ What skills, if any, will your employees need to work with advanced
technologies?
● Knowledge/ Organization. Who is driving the adoption of technology (leader/ title)?
What are XYZ doing? (How are they investing?)
○ What is your leadership and development strategy for this year? Next? Who
sets the priorities? Agenda?
○ How do you prepare people to work with technology, if at all? (Any mention
of reskilling? Working with technology? Augmenting skillets?)
○ What advice would you give leaders in large enterprises looking to prepare
their workforce for the future?
○ Any questions I should have asked? Tips for me?
Thank you and wrap up.
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Appendix B: Document Analysis Protocol
Website and Annual Reports
Organizational Information
• What are the values of the organization?
• What is the mission of the organization?
• Is there an “about us” section?
o What does the “about us” section say about culture?
o What are the published values of the organization (if listed)?
Reskilling or learning
• What is mentioned, or not mentioned, on the topic of learning?
o Is reskilling mentioned?
Resources
• What is listed regarding resources or budget around investments? In
technology? In learning?
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Appendix C: Credibility and Trustworthiness
The goal of this research was to understand the practical implications of the impact of
A.I. on the workforce and skills needed for the future. The ethics of the researcher are associated
with the credibility and trustworthiness of the research data (Merriam & Tisdell, 2009).
Credibility is influenced by the quality of the research protocols and the trustworthiness is
influenced by the research methods. The research methods influence the trustworthiness of the
data. To increase credibility and trustworthiness of this data, the researcher triangulated the data
by collecting information through interviews and documents. The research protocols (Appendix
A and Appendix B) were created to explore the key research questions of the study. Researcher
bias can also impact research credibility and trustworthiness. Maxwell (2013) noted bias does not
reduce the validity of data if the researcher acts with integrity in conducting their research. The
researcher took steps to mitigate potential bias in both data collection and data analysis by
following the research protocols and supporting the analysis with evidence.
THE IMPACT OF ADVANCED TECHNOLOGIES ON THE WORKPLACE AND THE
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Appendix D: Ethics
This study is “concerned with producing valid and reliable knowledge in an ethical
manner” (Merriman & Tisdell, 2016, p. 237). Every strategy was used to protect the research
participations from harm during the study. The careful design of the study aims to ensure the
trustworthiness and utilizing strategies for authenticity. Adhering to the highest research
standards, participants will be informed of the nature of the research during the recruitment of
participants. Significant attention will be used to highlight that research participation is voluntary
and that research participants can end their participation in the study at any time without penalty;
all details documented in an informed consent form provided at the beginning of the study.
Further ensuring the safety of the participants will be the submission and approval of the
University of Southern California Institutional Review Board (IRB). All IRB rules and
guidelines regarding study participant protocol will be followed throughout this study.
With regard to the data collected, all identifiable data will be deleted to ensure
organizational and individual confidentiality. Permission for audio recording will be obtained
before and at the start of the audio recording. Interviews that are audio recorded will be securely
kept until the files are sent for transcription in the cloud with password security. Following the
transcription of the recordings, all identifiable information will be removed, and the audio files
and full transcriptions will be deleted. Any documents collected during the interview will be
deleted and / or destroyed within two years of the dissertation defense.
As an employee of one of the organizations within the field being studied, this researcher
is aware of the challenges of studying an organization as an insider versus an outsider. Coughlin
and Brannick (2014) noted research on the inside involves researchers as “actors immersed in
local situations generating contextually embedded knowledge which emerges from experience”
THE IMPACT OF ADVANCED TECHNOLOGIES ON THE WORKPLACE AND THE
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101
versus an outsider perspective in which the researcher can study issues from a distance (p. 4).
However, the insider perspective can be valuable as it can shed light on the often-hidden
organizational realities (Coughlin & Brannick, 2014). Given that the researcher’s role within the
organization is not associated or connected to learning and development, the researcher’s role in
the interview will be that of a doctoral student/ researcher rather than stakeholder or associate,
and will follow all interview protocols and scripts.
Abstract (if available)
Abstract
Technical advancement is predicted to impact the workforce and will require the reskilling of many. This study sought to understand the preparations large enterprises are taking to prepare their workforce and their workplace for the impact of advanced technologies. Specifically, this paper explored the knowledge, motivation, and organizational influences that influence the Chief Learning Officer’s (CLOs) ability to prepare their workforce for the future. Clark and Estes’ (2008) gap analysis model influence the conceptual and methodological framework for the study along with the Burke-Litwin (1992) model for organizational change. Interviews were conducted with seven CLOs at large enterprises. ❧ The research explored the CLOs’ knowledge and motivation related to creating a leadership and development strategy to develop their workforce, considering their organizations’ adoption of advanced technologies. The data suggested CLOs are knowledgeable and motivated about preparing their workforce for the future of work. The research also explored how organizational culture and context supported or hindered CLO knowledge and motivation. The data suggested that indeed organizational cultural models and organizational cultural settings impact the CLOs’ ability to reach their goals. ❧ Recommendations for developing a transformational adult learning program for CLOs was proposed. The program design, metrics and critical behaviors needed to evaluate the effectiveness of the proposed program was influenced by Kirkpatrick model by also took an anagogical approach. The practices identified supported the continued development of knowledge, motivation and organizational cultures to help prepare large enterprises’ workforce and workplace for the impact of advanced technologies.
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Asset Metadata
Creator
Cooper, Carly E.
(author)
Core Title
The impact of advanced technologies on the workplace and the workforce: an evaluation study
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Organizational Change and Leadership (On Line)
Publication Date
03/01/2019
Defense Date
02/21/2019
Publisher
University of Southern California
(original),
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Tag
A.I.,artificial intelligence,CLO,collective efficacy,culture,efficacy,Knowledge,large enterprise,leadership,Learning and Instruction,learning transfer,machine learning,Motivation,OAI-PMH Harvest,organizational change,organizational culture,transformational learning,workforce,workplace
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Seli, Helena (
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), Schank, Roger (
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Tags
A.I.
artificial intelligence
CLO
collective efficacy
efficacy
large enterprise
learning transfer
machine learning
organizational change
organizational culture
transformational learning
workforce
workplace