MBA education

This study explores the perceptions of Iranian MBA graduates regarding the integration of AI into business education. Drawing on survey data from 379 alumni across a range of Iranian universities, the research assesses five core dimensions: perceived usefulness of AI, ethical concerns, faculty preparedness, job market implications, and interest in AI-focused coursework. The study also investigates whether demographic factors such as age, gender, income level, and marital status significantly influence these perceptions. Results indicate a generally favorable view of AI integration, with particularly strong support for incorporating AI coursework into MBA programs. Despite broad enthusiasm, respondents expressed concerns about data privacy, algorithmic bias, and the limited readiness of faculty to teach AI-related content. Inferential tests and path analysis reveal that demographic variables had little predictive power over AI perceptions or preferences, suggesting widespread acceptance across social strata. The findings underscore both the readiness of Iranian MBA graduates for AI-related curricular reform and the need for targeted institutional responses, including faculty development and ethical frameworks.

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.