Artificial Intelligence and HR Decision-Making: Implications for Managerial Judgment, Trust, and Fairness
Keywords:
artificial intelligence, human resource decision-making, managerial judgment, trust, fairness, HR analyticsAbstract
Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into human resource management (HRM), reshaping strategic HR decision-making across recruitment, performance appraisal, turnover prediction, and workforce planning. Despite the exponential growth of AI-related HR analytics research, there remains a theoretical gap in understanding how AI influences managerial judgment, trust in algorithmic outputs, and perceptions of fairness in HR decisions. Drawing on decision support systems theory, socio-technical systems perspectives, and insights from recent HRM scholarship, this paper develops a conceptual framework that situates HR decision-making as a human–AI collaborative process. The framework outlines the interrelationships between AI mechanisms, managerial interpretation, explainability, ethical governance, and the quality of HR decisions. We propose five research propositions that articulate conditions under which AI augments HR managerial judgment, fosters trust, and enhances procedural justice.
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References
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