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

Authors: Stefan Stieglitz; Nicholas R.J. Möllmann; Milad Mirbabaie; Lennart Hofeditz; Björn Ross

Addresses: Department of Computer Science and Applied Cognitive Science, University of Duisburg-Essen, Forsthausweg 2, 47057 Duisburg, Germany ' MAINGAU Energie GmbH, Department of Information Technology and Digital Transformation, Ringstr. 4-6, 63179 Obertshausen, Germany ' Department of Information Systems, Paderborn University, Warburger Str. 100 (Q3.128), 33098 Paderborn, Germany ' Department of Computer Science and Applied Cognitive Science, University of Duisburg-Essen, Forsthausweg 2, 47057 Duisburg, Germany ' School of Informatics, The University of Edinburgh, 10 Crichton Street, EH8 9AB, Edinburgh, UK

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.

DOI: 10.1504/IJMP.2023.132074

International Journal of Management Practice, 2023 Vol.16 No.4, pp.407 - 433

Accepted: 16 Aug 2021
Published online: 11 Jul 2023 *

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