Recommendations for Managing AI-Driven Change Processes: When Expectations Meet Reality

Stefan Stieglitz; Nicholas R. J. Möllmann (Frick); Milad Mirbabaie; Lennart Hofeditz; Björn Ross

doi:10.1504/IJMP.2023.132074

Recommendations for Managing AI-Driven Change Processes: When Expectations Meet Reality

Stefan Stieglitz, Nicholas R. J. Möllmann (Frick), Milad Mirbabaie, Lennart Hofeditz, Björn Ross

Research output: Contribution to journal › Article › peer-review

Abstract / Description of output

Artificial intelligence (AI) has moved beyond the planning phase in many organisations and it is often accompanied by uncertainties and fears of job loss among employees. It is crucial to manage employees’ attitudes towards the deployment of an AI-based technology effectively and counteract possible resistance behaviour. We present lessons learned from an industry case where we conducted interviews with affected employees. We evaluated our results with managers across industries and found that that the deployment of AI-based technologies does not differ from other IT, but that the change is perceived differently due to misguided expectations.

Original language	English
Pages (from-to)	407-433
Journal	International Journal of Management Practice
Volume	16
Issue number	4
DOIs	https://doi.org/10.1504/IJMP.2023.132074
Publication status	Published - 11 Jul 2023

Keywords / Materials (for Non-textual outputs)

artificial Intelligence
change management
resistance
AI-driven change
AI deployment
AI perception
AI

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Cite this

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title = "Recommendations for Managing AI-Driven Change Processes: When Expectations Meet Reality",

abstract = "Artificial intelligence (AI) has moved beyond the planning phase in many organisations and it is often accompanied by uncertainties and fears of job loss among employees. It is crucial to manage employees{\textquoteright} attitudes towards the deployment of an AI-based technology effectively and counteract possible resistance behaviour. We present lessons learned from an industry case where we conducted interviews with affected employees. We evaluated our results with managers across industries and found that that the deployment of AI-based technologies does not differ from other IT, but that the change is perceived differently due to misguided expectations. ",

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AU - Ross, Björn

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AB - Artificial intelligence (AI) has moved beyond the planning phase in many organisations and it is often accompanied by uncertainties and fears of job loss among employees. It is crucial to manage employees’ attitudes towards the deployment of an AI-based technology effectively and counteract possible resistance behaviour. We present lessons learned from an industry case where we conducted interviews with affected employees. We evaluated our results with managers across industries and found that that the deployment of AI-based technologies does not differ from other IT, but that the change is perceived differently due to misguided expectations.

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KW - AI deployment

KW - AI perception

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Recommendations for Managing AI-Driven Change Processes: When Expectations Meet Reality

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Keywords / Materials (for Non-textual outputs)

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