Open Access
Comprehensive Study on the Use of Artificial Intelligence to Minimize Bias in Healthcare Succession Management
4
Independent Researcher, California-USA
Abstract
In healthcare, succession planning mitigates the risk of leadership vacancies during retirements, turnover, and staffing shortages. However, current practices to choose a next leader often rely on subjective judgment, which can reinforce bias and limit fairness in leadership decisions. This study examines whether Artificial Intelligence (AI) can improve succession planning by supporting more objective and data-informed assessment of talent. The findings suggest that AI may help organizations define clearer criteria, identify high-potential candidates, and expand opportunities for underrepresented groups. At the same time, the study shows that AI must be used carefully, with strong data governance and collaboration among human resources professionals, data scientists, and clinical leaders. Without these safeguards, AI may reproduce the same biases it is meant to reduce. Used responsibly, AI has the potential to make healthcare leadership selection more transparent, equitable, and inclusive.
Keywords
artificial intelligence,
healthcare succession planning,
bias reduction,
leadership selection,
algorithmic fairness,
AI governance,
talent management,
ethical decision making
References
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