AI in Indian B-Schools: Generative AI Transforms Research & Teaching

Indian B-schools are rapidly adopting Generative AI in research and teaching, with a new MBAUniverse survey highlighting opportunities, challenges, and future trends.

The integration of Artificial Intelligence (AI), particularly Generative AI, into higher education has emerged as a transformative force, reshaping how institutions deliver learning and conduct research. Indian business schools (B-schools) are at the forefront of this evolution, leveraging AI to enhance teaching methodologies, streamline research processes, and redesign curricula to meet the demands of a rapidly changing global business landscape. A comprehensive survey conducted by MBAUniverse, unveiled at the 15th Indian Management Conclave (IMC 2025), provides an in-depth look into how AI is being adopted across India’s premier B-schools, including the Indian Institutes of Management (IIMs), Indian Institutes of Technology (IITs), Indian School of Business (ISB), Xavier Labour Relations Institute (XLRI), S.P. Jain Institute of Management and Research (SPJIMR), Management Development Institute (MDI), and Narsee Monjee Institute of Management Studies (NMIMS). This article explores the survey’s findings, highlighting AI’s impact on management education, faculty perceptions, and the challenges and opportunities that lie ahead.

Survey Overview and Methodology

The MBAUniverse survey, conducted among 235 faculty members from leading Indian B-schools, offers a detailed snapshot of AI adoption in management education. Released on September 29, 2025, during IMC 2025, the survey was inaugurated by Vineet Joshi, Secretary of Higher Education, and T.G. Sitharam, Chairman of the All India Council for Technical Education (AICTE). The study focused on faculty usage of Generative AI across key areas: research, teaching, curriculum development, student assessment, and administrative tasks. It also examined faculty perceptions of AI’s impact on student learning outcomes, skill development, and classroom engagement, alongside identifying critical challenges and opportunities for responsible AI integration.

The survey employed a quantitative approach, with faculty rating their AI usage on a scale of 1 to 5 (1 being minimal use and 5 being extensive use). Responses were collected from a diverse sample of institutions, ensuring representation from both public and private B-schools. The findings provide actionable insights for educators, administrators, and policymakers aiming to harness AI effectively in management education.

Key Findings: AI’s Role in B-Schools

1. Primary Applications of AI

The survey reveals that AI is most extensively utilized in research and teaching, with faculty rating their usage at 3.73/5 and 3.58/5, respectively. In research, AI tools are employed for data analysis, literature reviews, and generating insights from complex datasets, enabling faculty to produce high-quality research with greater efficiency. For instance, Generative AI models assist in synthesizing vast amounts of academic literature, identifying research gaps, and even drafting preliminary research frameworks.

In teaching, AI is transforming pedagogical approaches by enabling personalized learning experiences. Faculty use AI-driven tools to create interactive case studies, simulations, and real-time feedback mechanisms that enhance student engagement. Tools like AI-powered chatbots and virtual assistants help address student queries, breaking down barriers of language, background, or geography, as emphasized by Vineet Joshi during the survey’s release: “AI gives every student the freedom to ask questions and helps overcome barriers of language, background, or geography.”

Curriculum development is another area witnessing steady AI adoption, though at a slightly lower intensity compared to research and teaching. Faculty are leveraging AI to design courses that align with industry needs, incorporating emerging topics such as AI ethics, machine learning applications in business, and data-driven decision-making. However, AI’s use in student assessment and administrative tasks remains limited, with scores indicating nascent adoption. This suggests significant potential for growth in these areas, provided institutions invest in structured support and capacity-building initiatives.

2. Impact on Student Learning

Approximately 51.1% of faculty reported a favorable impact of AI on student learning outcomes, citing improvements in critical thinking, problem-solving, and analytical skills. AI tools enable students to engage with complex business scenarios through simulations and predictive models, fostering a deeper understanding of management concepts. For example, AI-driven platforms can simulate market dynamics, allowing students to test strategies in a risk-free environment.

However, the survey also highlights mixed perceptions. About 21.3% of faculty indicated it was too early to assess AI’s full impact, reflecting the relatively recent adoption of these technologies. Meanwhile, 18.1% reported an unfavorable impact, potentially due to concerns about over-reliance on AI tools or challenges in integrating them effectively into teaching. A smaller subset (9.6%) observed no significant impact, suggesting variability in how AI is implemented across institutions.

3. Faculty Proficiency and Capacity Building

The survey categorizes faculty based on their AI proficiency: 55% identify as intermediate users, 7% as experts, and the remainder as beginners. This distribution underscores a critical need for structured capacity-building programs to enhance faculty skills in AI adoption. Intermediate users are comfortable with basic AI tools but may lack the expertise to leverage advanced functionalities, such as customizing AI models for specific research or teaching needs. Expert users, though a minority, serve as pioneers, demonstrating the potential of AI to transform management education.

Institutions can address this gap by offering targeted training programs, workshops, and certifications focused on AI applications in academia. Collaborative initiatives with industry partners and AI technology providers could further bridge the knowledge gap, ensuring faculty are equipped to integrate AI responsibly and effectively.

4. Future Expectations

Over half of the surveyed faculty anticipate an increased role for AI in teaching, curriculum design, and research over the next 12 months. This optimism reflects the growing recognition of AI’s potential to enhance educational outcomes and streamline academic processes. Faculty expect AI to play a pivotal role in developing adaptive learning systems, where course content is tailored to individual student needs, and in advancing research through sophisticated data analytics and predictive modeling.

Challenges in AI Adoption

Despite its transformative potential, AI adoption in B-schools faces several challenges, as identified by the survey:

• Ethical and Integrity Concerns: The most frequently cited challenge (192 responses) is the ethical implications of AI use, particularly in research. Issues such as plagiarism, data manipulation, and the risk of AI-generated content lacking originality raise concerns about academic integrity. Faculty emphasize the need for clear ethical guidelines to ensure AI is used responsibly.

• Inaccuracies and Unreliable Outputs: A significant number of respondents (152) highlighted inaccuracies in AI-generated outputs, such as factual errors or biased results. This underscores the importance of validating AI outputs and integrating human oversight to maintain quality and reliability.

• Lack of Regulatory Policy: With 112 responses, the absence of clear regulatory frameworks for AI use in education was a notable concern. Faculty call for institutional and national policies to guide AI adoption, ensuring alignment with academic standards and ethical principles.

Opportunities for Responsible AI Integration

The survey’s findings highlight several opportunities for B-schools to harness AI responsibly:

• Enhanced Student Engagement: AI tools can create dynamic, interactive learning environments, such as virtual simulations and gamified case studies, that cater to diverse learning styles. These tools foster greater student engagement and improve retention of complex concepts.

• Personalized Learning Pathways: AI enables adaptive learning systems that tailor content to individual student needs, addressing gaps in understanding and accelerating skill development. This is particularly valuable in management education, where students come from varied academic and professional backgrounds.

• Streamlined Research Processes: AI can automate time-consuming tasks like literature reviews and data analysis, allowing faculty to focus on higher-order research activities. This enhances research productivity and supports the development of cutting-edge management theories.

• Administrative Efficiency: While currently underutilized, AI has the potential to streamline administrative tasks such as scheduling, resource allocation, and student record management, freeing up faculty time for teaching and research.

Government and Institutional Support

The Indian government’s commitment to integrating AI into education, as articulated by Vineet Joshi, aligns with the broader vision of Viksit Bharat (Developed India). Initiatives like the National Education Policy (NEP) 2020 emphasize technology-driven education, and AI is poised to play a central role in achieving these goals. The government is investing in infrastructure, training, and policy frameworks to support AI adoption across educational institutions.

B-schools, in turn, must establish internal policies to guide AI use, addressing ethical concerns and ensuring alignment with academic standards. Partnerships with AI technology providers and industry stakeholders can further enhance access to cutting-edge tools and expertise.

The MBAUniverse survey underscores the transformative impact of Generative AI on Indian B-schools, particularly in research and teaching, with growing applications in curriculum design. While faculty are optimistic about AI’s potential, challenges such as ethical concerns, unreliable outputs, and the lack of regulatory policies must be addressed to ensure responsible adoption. By investing in faculty training, developing clear guidelines, and leveraging AI’s capabilities, B-schools can position themselves at the forefront of management education innovation. As AI continues to evolve, its integration into B-schools will not only enhance learning outcomes but also prepare students to thrive in an AI-driven business world.