Optimizing employee roles in the era of generative AI: a multi-criteria decision-making analysis of co-creation dynamics

Artificial Intelligence (AI) has the ability to transform the way organizations operate, but imposes a unique challenge for them. Adoption of AI might reshape the human resource management patterns which calls for optimization of roles in workplaces for dealing with technology. Critical decision points and alternatives are identified through a systematic review of literature and Analytical Hierarchy Approach (AHP) is applied to analyze their priority weights. The results of AHP model indicate adaptive organization structure, specialized AI teams, ethics oversight and governance and innovation infrastructure to be significant in AI integration. Furthermore, sensitivity analysis technique is employed to examine the robustness of the decision outcomes at varying criteria weights and the results shows no significant impact on the ranks indicating robustness of the decision achieved if the criteria weight changes on the overall optimization process. This study contributes to expanding discussion on workforce transformation in AI era.

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Publication Details

Journal
Cogent Social Sciences
Published
2025-03-16
DOI
https://doi.org/10.1080/23311886.2025.2476737
Citations
3
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
3.73
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article

Optimizing employee roles in the era of generative AI: a multi-criteria decision-making analysis of co-creation dynamics

Alpana Agarwal
3 citations
Cogent Social Sciences
Digital Transformation in Industry
3.73
article

Optimizing employee roles in the era of generative AI: a multi-criteria decision-making analysis of co-creation dynamics

Alpana Agarwal
article en
3 citations

Abstract

Artificial Intelligence (AI) has the ability to transform the way organizations operate, but imposes a unique challenge for them. Adoption of AI might reshape the human resource management patterns which calls for optimization of roles in workplaces for dealing with technology. Critical decision points and alternatives are identified through a systematic review of literature and Analytical Hierarchy Approach (AHP) is applied to analyze their priority weights. The results of AHP model indicate adaptive organization structure, specialized AI teams, ethics oversight and governance and innovation infrastructure to be significant in AI integration. Furthermore, sensitivity analysis technique is employed to examine the robustness of the decision outcomes at varying criteria weights and the results shows no significant impact on the ranks indicating robustness of the decision achieved if the criteria weight changes on the overall optimization process. This study contributes to expanding discussion on workforce transformation in AI era.

Cogent Social SciencesVol. 11(1)
Symbiosis International University (IN)
Openalex Percentile: Top 8%
Digital Transformation in Industry
3.73
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