Most B-school faculty in India lack AI expertise: Survey
28 Sep 2025

A recent survey by MBAUniverse.com has revealed that while Indian business schools are rapidly adopting artificial intelligence (AI) technology, a majority of the faculty members still lack the necessary expertise.

The study surveyed 235 educators from top institutions such as IIMs, IITs, ISB, XLRI, and SPJIMR.

It found that only 7% of these educators consider themselves expert users of AI tools.

Growing acceptance of AI in academia
Survey findings

The survey also revealed that only 51% of the faculty members are confident about the positive impact of AI adoption on business school students.

Despite this, more than half of them expect an increase in AI's role in teaching, curriculum design, and research over the next year.

This indicates a growing acceptance and anticipation for further integration of AI into academic processes.

Transformative potential of AI in management education
Application areas

The survey found that faculty members are using AI mostly for research and teaching purposes. However, its application in curriculum development is also growing steadily.

Administrative tasks and student assessment are still emerging areas of AI use, presenting opportunities for structured support and capacity building programs.

This highlights the potential of AI to transform various aspects of management education beyond just teaching.

Faculty perceptions and tool preferences
Perception insights

The survey also explored faculty perceptions about AI's impact on student learning, skill development, and classroom engagement.

It also looked at the tools, training, and policy guidance they deem most important for responsible adoption of AI.

Notably, ChatGPT was rated as the most relevant tool for teaching-related activities by a majority of faculty members.

Challenges and concerns in AI adoption
Impact assessment

While most faculty members viewed the impact of AI use on student learning positively, 21% said it was too early to tell.

Meanwhile, 18% saw an unfavorable impact, and nearly 10% reported no significant effect.

The main challenge in research-related use of generative AI was ethical concerns followed by inaccuracies/unreliable outputs and lack of regulatory policy.