The rapid advancement of generative artificial intelligence (AI) is fundamentally transforming workplace learning and development, reshaping how organizations build skills, manage knowledge, and support continuous professional growth. As skill obsolescence accelerates and demand for personalized, scalable, and cost-effective learning intensifies, AI-enabled learning systems are increasingly positioned as strategic responses to evolving work models and workforce needs. Existing research demonstrates that AI-enhanced learning can improve creativity, knowledge retention, and training efficiency, while enabling new forms of formal and informal learning within organizations. However, the integration of generative AI also raises critical concerns regarding professional expertise, human judgment, ethical responsibility, and the reconfiguration of traditional training and development models. This study adopts a qualitative approach to synthesize contemporary theoretical and empirical literature to examine how generative AI is reshaping individual and organizational learning processes, influencing professional competencies, and altering the balance between structured programmes and adaptive, on-demand learning. It further explores how contextual factors, including e-HRM systems, skills mismatches, generational dynamics, and job satisfaction, mediate the impact of AI-driven learning initiatives. By critically analyzing opportunities and risks, the paper contributes a nuanced understanding of AI-mediated workplace learning and offers insights into how organizations can align digital transformation with sustainable workforce development. The study advances scholarships on AI and learning while informing practitioners and policymakers on designing effective, inclusive, and ethically grounded AI-integrated learning strategies.

Keywords

AI, Training, Workforce, Organization, Workplace.