Employee involvement in AI-driven HR decision-making: A systematic review

Abstract

Orientation: The integration of artificial intelligence (AI) into human resource management (HRM) is transforming decision-making processes and employee involvement.

Research purpose: This study examines AI-driven decision-making in HRM, with a focus on employee involvement and ethical challenges.

Motivation for the study: As AI adoption in HRM rapidly grows, it is crucial to understand its implications for organisational practices and employee experiences.

Research approach/design and method: This study conducted a systematic review of 193 peer-reviewed articles (2019–2023), employing cluster analysis to identify four key themes in AI-driven HRM.

Main findings: The study identifies four clusters: AI adoption, highlighting employee involvement in smooth transitions; AI Ethics, focussing on transparency and fairness; AI-driven human resource decision-making, showing enhanced recruitment and performance management; and AI performance, emphasising operational efficiency through AI systems.

Practical/managerial implications: The findings highlight the role of employee involvement in successful AI transitions, emphasising its impact on acceptance and operational success.

Contribution/value-add: This review also suggests future research directions, emphasising the need to explore AI’s long-term impacts on organisational culture and employee satisfaction.