Purpose-Rapid digitalization is reshaping how organizations manage and motivate their workforce. China’s private healthcare sector faces severe retention challenges; at Jiahui Healthcare, the workforce declined from 408 in 2021 to 330 in 2023, with retention falling from 80% to 64%. This study examines how artificial intelligence (AI) and digital analytics can inform tenure-based incentive systems that strengthen employee retention. Methodology-A participatory action-research project was conducted at Jiahui Healthcare involving two sequential interventions: an Enhanced Talent Management Program (ETMP) and a digitally engineered Retention-Linked Incentive Program (RLIP). The RLIP employed a human resource information system (HRIS) to track tenure milestones and automate rewards, while exploring the role of AI-driven analytics and predictive algorithms in tailoring incentives and identifying attrition risks. Findings-The interventions achieved a 22% reduction in turnover intention and improved perceptions of digital equity. Results indicate that integrating developmental initiatives with transparent, digitally enabled incentive systems provides a more effective response to retention pressures than either approach alone. Value-The study contributes to the growing field of digital human resource management by demonstrating how participatory action research and AI-enabled incentive design can deliver practical solutions to workforce retention. It highlights the potential of combining developmental programs with predictive, technology-driven tools to sustain engagement in high-pressure service environments.
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