Recommendations for managing AI-driven change processes: when expectations meet reality

Stefan Stieglitz, Nicholas R.J. Möllmann, Milad Mirbabaie, Lennart Hofeditz and Björn Ross

International Journal of Management Practice, 2023, vol. 16, issue 4, 407-433

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' 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.

Keywords: artificial intelligence; AI; change management; resistance; AI-driven change; AI deployment; AI perception. (search for similar items in EconPapers)
Date: 2023
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