The Impact of AI and Automation Policies on Employee Development: A Thematic Approach

Over the past few years, automation and artificial intelligence (AI) have become more active in transforming the global labour market and redefining industries, organisational forms, and employment relationships. The traditional job role is also altered by the introduction of new technologies into the workplace, necessitating a reevaluation of policies that govern training, reskilling, and career advancement. This qualitative paper examines the effects of these technological advancements on employee development, with a particular focus on job transformation and reskilling, as well as psychological adjustments and organisational response. The selection of a secondary method of data collection, rather than a primary method (interview or survey), was influenced by the fact that the research topic involves the analysis of policies, reports, case studies, and academic literature that are dedicated to the issues of AI, automation, and employee development. It employs a thematic approach to emphasise emergent trends and issues in technologically induced workspaces. A thematic analysis method was employed to identify patterns, ideas that tend to recur, and significant discoveries in the data that was collected. The findings refute the notion that, despite the fact that AI and automation increase productivity and stimulate innovation, they also underscore the importance of ongoing learning and adaptability for employees. The traditional employment roles are in the process of being transformed, and there is an increasing demand for interpersonal, analytical, and digital skills. Nevertheless, the disparity in access to training programs poses a threat to the development of even more profound skill gaps and exacerbates inequalities, particularly among more vulnerable workers. Simultaneously, the psychological aspect of technological change, which includes the apprehension of losing one's job and the reluctance to learn new tools, is also a significant impediment to the seamless transition. It is evident from these results that the efficient development of the workforce in technology-driven environments is contingent upon the strategic alignment of human resource practices and technology adoption. Companies and organisations that establish an inclusive learning environment, open communication patterns, and reskill their program design are more likely to increase employee engagement and retention. This research concludes with practical recommendations for policymakers and organisations to establish a workforce that is future-ready, adaptable, and flexible in the context of AI and automation. The efficacy of AI and automation will be contingent upon the capacity of organisations and policymakers to foster their growth by emphasising employee development, despite their transformative potential.

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Publication Details

Journal
Current Journal of Applied Science and Technology
Published
2025-08-16
DOI
https://doi.org/10.9734/cjast/2025/v44i84592
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

The Impact of AI and Automation Policies on Employee Development: A Thematic Approach

Ademeso Tosin Success, Nduonofit Okon Isana
1 links
Current Journal of Applied Science and Technology
Impact of AI and Big Data on Business and Society
article

The Impact of AI and Automation Policies on Employee Development: A Thematic Approach

Ademeso Tosin Success, Nduonofit Okon Isana
article en

Abstract

Over the past few years, automation and artificial intelligence (AI) have become more active in transforming the global labour market and redefining industries, organisational forms, and employment relationships. The traditional job role is also altered by the introduction of new technologies into the workplace, necessitating a reevaluation of policies that govern training, reskilling, and career advancement. This qualitative paper examines the effects of these technological advancements on employee development, with a particular focus on job transformation and reskilling, as well as psychological adjustments and organisational response. The selection of a secondary method of data collection, rather than a primary method (interview or survey), was influenced by the fact that the research topic involves the analysis of policies, reports, case studies, and academic literature that are dedicated to the issues of AI, automation, and employee development. It employs a thematic approach to emphasise emergent trends and issues in technologically induced workspaces. A thematic analysis method was employed to identify patterns, ideas that tend to recur, and significant discoveries in the data that was collected. The findings refute the notion that, despite the fact that AI and automation increase productivity and stimulate innovation, they also underscore the importance of ongoing learning and adaptability for employees. The traditional employment roles are in the process of being transformed, and there is an increasing demand for interpersonal, analytical, and digital skills. Nevertheless, the disparity in access to training programs poses a threat to the development of even more profound skill gaps and exacerbates inequalities, particularly among more vulnerable workers. Simultaneously, the psychological aspect of technological change, which includes the apprehension of losing one's job and the reluctance to learn new tools, is also a significant impediment to the seamless transition. It is evident from these results that the efficient development of the workforce in technology-driven environments is contingent upon the strategic alignment of human resource practices and technology adoption. Companies and organisations that establish an inclusive learning environment, open communication patterns, and reskill their program design are more likely to increase employee engagement and retention. This research concludes with practical recommendations for policymakers and organisations to establish a workforce that is future-ready, adaptable, and flexible in the context of AI and automation. The efficacy of AI and automation will be contingent upon the capacity of organisations and policymakers to foster their growth by emphasising employee development, despite their transformative potential.

Current Journal of Applied Science and TechnologyVol. 44(8)
Nile University of Nigeria (NG), University of Abuja (NG)
Openalex Percentile: Top 74%
Impact of AI and Big Data on Business and Society
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