Transformative Learning Through Organizational Learning Theory in the Gen-AI Landscape: Challenges and Capacities for Organizational Evolution

Generative artificial intelligence (Gen-AI) marks a transformative phase for organizations, creating both major opportunities and challenges. Anchored in organisational learning theory, this study examines how organizations adopt Gen-AI by unpacking the related challenges, learning processes, and required capabilities. Using a multiple-case study design with semistructured interviews across four pioneering organizations, the research highlights the importance of adaptability, rapid decision-making, risk tolerance, and a strong learning culture in shaping organizational learning during Gen-AI adoption. The findings show that Gen-AI creates distinctive learning demands compared with earlier technologies. Its cognitive reasoning and adaptive functionalities require organizations to engage in iterative, continuous learning to integrate these tools into both strategic and operational systems. The study offers practical guidance for organizations seeking to overcome adoption challenges, strengthen learning cultures, and realize Gen-AI’s transformative potential. It also contributes to the broader Gen-AI discourse by providing a theoretically grounded and empirically supported roadmap for managing AI integration, including strategies such as iterative feedback loops, risk-tolerant decision-making, and embedding ethical considerations in AI governance.