Reframing Human Resource Governance through Artificial Intelligence: A Legitimacy-Based Model for Public Healthcare Workforce Transformation in Poland

Abstract

Artificial Intelligence (AI) is increasingly transforming healthcare systems, yet its integration into public-sector human resource management (HRM) remains limited. Polish public healthcare institutions face persistent workforce shortages, administrative inefficiencies, and rising demographic pressure. This study develops a governance-centered framework to evaluate how AI adoption can enhance workforce intelligence, recruitment efficiency, strategic workforce planning, and organisational resilience while maintaining compliance with GDPR and public accountability standards. Unlike prior research focused on private-sector HR, this paper conceptualises AI-enabled HR transformation as a shift from administrative to anticipatory workforce governance. Grounded in Institutional Theory, the Resource-Based View (RBV), and Strategic Human Capital Theory, the study proposes the Prestini Artificial Intelligence for Healthcare Human Resources (P-AIHR) Framework. The model integrates five pillars: workforce intelligence analytics, AI-assisted recruitment, ethical governance and compliance, adaptive workforce development, and executive decision support. A phased 36-month implementation roadmap and a structured risk–mitigation matrix are presented. The findings suggest that AI in public healthcare HR should operate as a hybrid system combining predictive analytics with human oversight to preserve legitimacy and trust. The study contributes a structured conceptual model tailored to Central and Eastern European public healthcare systems, offering theoretical, managerial, and policy insights into responsible AI adoption. This study extends algorithmic governance theory into public healthcare HR systems within regulated European contexts by operationalising legitimacy-preserving AI architecture.

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