Responsible AI Governance and Talent Development

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Artificial intelligence is reshaping talent development through skills analytics, personalized learning, AI-supported coaching, competency assessment, career development, internal mobility, and workforce planning. These applications can expand access to development and strengthen workforce capability, but they also create legal, ethical, social, and environmental responsibilities that efficiency-oriented approaches do not fully address. This study examines how ten influential global AI governance instruments align with the five dimensions of Socially Responsible Artificial Intelligence (SRAI): economic, legal, ethical, philanthropic, and environmental responsibility. Using comparative policy analysis, the study evaluates policy ideas, institutional force, and implementation instruments and then translates the observed patterns into governance requirements for AI-enabled talent development. The analysis shows strong convergence around human oversight, transparency, fairness, accountability, and capability building, while employee participation, equitable access to development, community learning, and environmental accountability remain unevenly institutionalized. Building on these findings, the article develops an SRAI-informed governance architecture linking global norms to learning-data governance, fair competency assessment, explainable career recommendations, continuous reskilling, worker voice, community capability building, and resource-aware learning systems. The framework positions responsible talent development as an organizational mechanism for creating workforce capability, lifelong employability, social inclusion, and sustainable value, thereby connecting AI governance with Common-Good Human Resource Management.