Alina Köchling, Marius Claus Wehner, Sascha Alexander Ruhle
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This (AI)n’t fair? Employee reactions to artificial intelligence (AI) in career development systems
Organizations increasingly implement AI for career development to enhance efficiency. However, there are concerns about employees’ acceptance of AI and the literature on employee acceptance of AI is still in its infancy. To address this research gap, integrating justice theory, we investigate the effects of the deciding entity (human, human and AI, and AI) and the impact of the data source (internal data, external data), on employees’ reactions. Using a scenario-based between-subject design, displaying a common situation in organizations (N = 280) and an additional causal-chain-approach (N = 157), we examined whether a decrease of human involvement in decision making diminishes employees’ perceived fairness and satisfaction with the career development process and increases their perceived privacy intrusion. Although we also considered other data sources to moderate the proposed relationships, we found no support for interaction effects. Finally, fairness and privacy intrusion mediated the influence of the deciding entity and data source on turnover intention and employer attractiveness, while satisfaction with the process did not. By addressing how the employees react to AI in career development–showing the negative reactions, our study holds considerable relevance for research and practice.
期刊介绍:
Review of Managerial Science (RMS) provides a forum for innovative research from all scientific areas of business administration. The journal publishes original research of high quality and is open to various methodological approaches (analytical modeling, empirical research, experimental work, methodological reasoning etc.). The scope of RMS encompasses – but is not limited to – accounting, auditing, banking, business strategy, corporate governance, entrepreneurship, financial structure and capital markets, health economics, human resources management, information systems, innovation management, insurance, marketing, organization, production and logistics, risk management and taxation. RMS also encourages the submission of papers combining ideas and/or approaches from different areas in an innovative way. Review papers presenting the state of the art of a research area and pointing out new directions for further research are also welcome. The scientific standards of RMS are guaranteed by a rigorous, double-blind peer review process with ad hoc referees and the journal´s internationally composed editorial board.