Management learning

The integration of artificial intelligence into Master of Business Administration (MBA) education is reshaping the foundations of management learning worldwide. This study conducts a qualitative meta-synthesis of 17 peer-reviewed sources published between 2001 and 2021 to examine how AI technologies—ranging from generative models and adaptive learning systems to predictive analytics and federated learning—are influencing MBA curricula, pedagogy, student engagement, and institutional strategies. Findings reveal that AI holds transformative potential for enhancing personalization, academic performance, and curriculum relevance, while also addressing enrollment challenges and labor market misalignments. However, integration remains uneven and fraught with ethical, infrastructural, and pedagogical challenges, including concerns over academic integrity, faculty preparedness, and digital equity. Conceptual frameworks such as the Technology Acceptance Model (TAM), paradox theory, and interpretive structural modeling elucidate the enabling and constraining factors surrounding AI adoption. The study highlights the urgent need for business schools to pursue a holistic and ethically grounded AI strategy that balances technological innovation with humanistic leadership development. Ultimately, AI is not only redefining how MBAs are delivered, but also reorienting their purpose toward preparing future-ready leaders for complex, data-driven environments. The paper concludes with a call for adaptive, inclusive, and ethically sound educational reforms in MBA programs worldwide.