AI Education in India: Student Demand Surges, Faculty Shortage Alarming

Breakfast that’s actually F-A-S-T

No more sad granola bars or sprinting out the door with just coffee.

Huel Black Edition is a ready-in-seconds shake packed with: 40g protein, 6g+ fiber, 0 prep. Just shake, sip, go.

Get 15% off your first order + a free t-shirt and shaker with code HUELSPRING, for orders over $75.

Try Huel today

India is witnessing a dramatic surge in demand for Artificial Intelligence (AI) education, particularly at the undergraduate level. However, this rapid rise in interest is being matched by a worrying shortage of qualified faculty, raising concerns about the sustainability and quality of AI education across the country.

In Tamil Nadu, one of India’s most active hubs for engineering education, the intake for undergraduate courses in AI and Data Science has more than doubled within three years — from 7,049 students in 2022-23 to 15,702 in 2024-25. This trend reflects a national shift toward AI-focused careers, fueled by increasing awareness and opportunities in automation, machine learning, and data-driven technologies.

According to estimates, India now offers nearly 800 B.Tech courses in AI through various engineering institutions. However, the number of qualified AI educators has not kept pace. This gap is proving to be a major obstacle in delivering quality instruction to the growing student population.

Dr. Balaraman Ravindran, Head of the Department of Data Science and AI at IIT Madras, notes that while AI is built on the foundations of Computer Science, it relies heavily on advanced mathematical concepts and algorithmic thinking. He emphasizes that faculty must possess specialized knowledge in these areas to teach AI effectively. "Computer Science alone does not cover the depth required for AI. Instructors must have a strong grasp of mathematics and statistics to build and explain AI models," he said.

Dr. Subalalitha C.N., Professor in the Department of Computing Technologies at SRM Institute of Science and Technology (SRMIST), agrees. SRMIST offers ten AI-focused programs, but recruiting qualified faculty remains a persistent challenge. “Many of our faculty members are enhancing their expertise through certifications and Faculty Development Programmes (FDPs). With more students opting for AI, upskilling is not optional — it’s a necessity,” she said.

Adding to the complexity, many institutions are now adopting a multidisciplinary approach, integrating AI with traditional engineering subjects. This model not only facilitates funding and innovation but also reflects the evolving nature of AI applications across industries. “AI is deeply mathematical. It blends naturally with core subjects, making integration easier,” Dr. Subalalitha noted.

The shortage of AI educators is not just a logistical problem — it is a structural one. Industry experts suggest that collaboration between academia and industry could partially address the issue, by bringing experienced professionals into classrooms, either as guest lecturers or adjunct faculty. However, a long-term solution would require the development of a comprehensive faculty training roadmap and strategic efforts to encourage young AI experts to consider careers in academia.

AI development is not one-size-fits-all. While developers building applications might not need deep mathematical knowledge, those creating language models or machine learning algorithms certainly do. This diversity in roles demands tailored educational approaches and specialized training for educators.

In conclusion, India stands at a critical juncture. The enthusiasm for AI education is undeniable, but without a parallel investment in teacher training and academic infrastructure, the country risks diluting the very quality of expertise it seeks to build. Bridging this gap between student demand and faculty supply is essential to unlocking India’s potential as a global AI powerhouse.