Beyond Coding: India's Engineering Colleges Must Teach Judgement In The AI Age

A third-year civil engineering student submits code for a flood-warning model. It runs perfectly; an AI assistant wrote it in seconds. Then her teacher asks three questions. What rainfall data does the model assume? What happens if a river gauge fails? What does a false alarm cost a district administration that must evacuate a village? If she cannot answer, the code is not engineering. It is a guess with good formatting.

That scene captures the most important idea in a recent Nikkei Asia interview with Daniel Diermeier, chancellor of Vanderbilt University. Cheating with AI, he argued, has a "very simple solution": oral examinations after students submit their work. The harder problem is mastery. "The danger is people will not do the hard work anymore," he warned. The tools can become "crutches".

For India, with its IITs, NITs and thousands of AICTE-approved engineering colleges, the question is sharper still. How do we produce engineers who use AI fluently and also take responsibility for what it produces?

The University In The Arena

Diermeier's interview is also a reminder that universities now sit inside geopolitics. As the United States and China race for AI leadership, American campuses face tighter rules on foreign influence, conflicts of interest and dual-use technology. Vanderbilt, he disclosed in Tokyo, spends more than $300 million a year on compliance with various federal regulations, out of operating revenue of $2.02 billion. Collaboration with Chinese entities, he conceded, is now "practically no".

Vanderbilt has responded by building, not retreating. In 2024 it launched an Institute of National Security under retired General Paul Nakasone, to help "policymakers understand technology, and technologists understand policies". Diermeier borrows his frame from Claudia Goldin and Lawrence Katz's book The Race between Education and Technology: education must keep pace with technology, or opportunity is lost.

India should draw two lessons. Research security is real, and it will matter more as Indian campuses enter semiconductors and AI. But India need not import American-scale compliance bureaucracy; it can design proportionate systems that fit its institutions. And as Diermeier notes, universities that lose public trust become "an attractive target for politicians". Indian institutions can earn trust the surest way: by being visibly useful.

The Foundations Are In Place

The good news is that India is not starting from zero. The National Education Policy 2020 anticipated this moment, foreseeing demand for mathematics, computer science and data science alongside multidisciplinary abilities across the sciences, social sciences and humanities. It asked that AI be introduced as a contemporary subject.

The government has followed up with money and infrastructure. The Union Cabinet approved the IndiaAI Mission in March 2024 with an outlay of ₹10,371.92 crore. By February 2026 the mission offered more than 38,000 high-end GPUs at about ₹65 per GPU-hour, with 20,000 more announced. That is compute few colleges could ever afford on their own. The Ministry of Education sanctioned ₹990 crore for three AI Centres of Excellence in healthcare, agriculture and sustainable cities, led by AIIMS Delhi, IIT Delhi, IIT Ropar and IIT Kanpur. The 2025 budget added a ₹500 crore Centre of Excellence in AI for education.

AICTE declared 2025 the "Year of Artificial Intelligence" and has begun weaving AI into core branches; electrical engineering curricula have been revised, and committees are working on civil, mechanical and electronics. Research spending is rising: gross expenditure on R&D reached ₹2.45 lakh crore in 2023-24, or 0.84 per cent of GDP, and for the first time private industry spent more than government. That share is still well below what China or the United States invest, which is why the ₹1 lakh crore Research, Development and Innovation scheme, approved in July 2025 and run through the Anusandhan National Research Foundation, matters. Semicon 2.0, approved in July 2026 with ₹1,27,500 crore, names talent as one of its six pillars; 315 universities already teach chip design on industry-standard tools, and about 68,000 students have been trained.

The architecture exists. The task now is to carry it from the premier institutes to the wider college system.

What The World Is Teaching

Leading institutions abroad offer fewer signals in their degree titles than in their design. From August 2026, the National University of Singapore made AI courses compulsory for all undergraduates, and every major now includes at least one course on how AI is changing that profession. AI fluency is treated as a requirement for every branch, not a privilege of computer science.

MIT's Common Ground for Computing Education, launched in 2020, builds courses jointly with other departments; Modelling with Machine Learning, for instance, was developed with engineering departments. AI is taught inside disciplines, not beside them. The Technical University of Munich ties machine intelligence to robotics through its Munich Institute of Robotics and Machine Intelligence, a model suited to India's manufacturing ambitions. Tsinghua University opened a dedicated College of AI in April 2024. In France, the Hi! The PARIS cluster, led by Institut Polytechnique de Paris and HEC Paris with Inria and CNRS, won €70 million under France 2030 to bring engineers, economists and managers together. Britain's Isambard-AI at Bristol and Dawn at Cambridge form a national AI research resource: compute as shared public infrastructure.

India's IndiaAI GPU pool rests on the same idea. The challenge is to make it reachable from a college in Kohima as easily as from a lab in Bengaluru.

India's Own Map

India's map is more encouraging than the usual metropolitan story suggests. In Jammu and Kashmir, IIT Jammu hosts the central project management unit for the Ministry of Education's AI Centres of Excellence, whose call offered ₹2 crore in seed funding to each of 15 consortia. In Nagaland, NIT Nagaland ran an AICTE-ATAL faculty development programme on AI and machine learning, the kind of route through which Northeast teachers can retool. In Assam, IIT Guwahati's Mehta Family School of Data Science and AI has offered degrees since 2021, while Tata's ₹27,000 crore chip assembly and test unit at Jagiroad gives the region an industrial anchor for that talent.

In West Bengal, IIT Kharagpur turned its AI Centre of Excellence into a full Department of AI in 2024. In Goa, the state’s Directorate of Higher Education partnered with IIITDM Jabalpur to run AI-in-teaching programmes for faculty across 69 disciplines, aiming to reach about 500 teachers. In Gujarat, Micron's $2.75 billion assembly and test facility at Sanand opened in early 2026, and the Tata–PSMC fab at Dholera, India’s first commercial chip fab, is under construction, with production expected around 2028. In Chennai, IIT Madras's Nilekani Centre at AI4Bharat builds open datasets and models for Indian languages. In Uttar Pradesh, IIT Kanpur's Airawat Research Foundation applies AI to air quality, mobility, energy, water and waste in cities.

These are strong hubs. What is missing are the spokes: systematic links between them and the AICTE colleges nearby, where most of India's engineering students actually study.

Rigour And Responsibility

Two disciplines must hold this together. The first is engineering rigour. AI-assisted assignments should be paired with oral defence, laboratory demonstration and a written log of how outputs were verified. A civil engineer should stress-test an AI flood model; an electrical engineer should validate a grid forecast against measured load; a mechanical engineer should check an AI-generated design against physical principles. Mathematics, physics and uncertainty analysis are not old-fashioned. They are what let an engineer recognise when AI is wrong.

The second is proportionate research security. As Indian campuses take on semiconductor and AI work, they need partner due diligence, conflict-of-interest disclosure and sound data stewardship. Smaller colleges cannot build Vanderbilt-style compliance offices; shared national help desks can do that work for them.

Five Steps For The Government And AICTE

First, a common AI competency framework for every engineering branch. Building on the Year of AI and its branch committees, AICTE and the Ministry of Education should define outcomes in AI literacy, application within the discipline, verification and ethics, and assess them through project defence rather than written recall.

Second, hub-and-spoke partnerships. The Centres of Excellence and the IIT Jammu coordination unit offer a ready structure to fund shared laboratories, visiting faculty and joint projects linking IITs and NITs with surrounding colleges, with priority for Jammu and Kashmir, other Himalayan States. Union Territory of Ladakh and the Northeast. Success should be measured by completed joint work, not memoranda signed.

Third, faculty development that changes classrooms. ATAL programmes should become sustained course redesign, with funded time and mentoring. Goa's discipline-by-discipline model deserves scaling. The metric is classroom adoption, not attendance.

Fourth, open the national infrastructure to tier-2 and tier-3 colleges. A simple, supported route to IndiaAI compute, an expanded chip-design network under Semicon 2.0, and shared research-security advisory desks would let a modest college do serious work.

Fifth, mission-linked challenge grants. Through the Anusandhan National Research Foundation, fund college teams working with municipalities, MSMEs, cooperatives and the new chip plants on water, clean manufacturing, agriculture and Indian-language tools. Require validation and a route to adoption, and publish the results so public money builds public trust.

Judgement Is The measure

Return to the student with her flood model. The goal is not that she writes less code, but that she can explain it, test it and stand behind it when a district's safety depends on it.

Diermeier says American universities are struggling with a loss of public trust. India has the chance to avoid that fate. NEP 2020, the IndiaAI Mission, the Centres of Excellence and Semicon 2.0 have laid the groundwork. India's AI promise will be met not in its 23 IITs alone, but when thousands of engineering colleges can turn AI into reliable solutions for citizens. That is the race between education and technology that India must win.

About the Authors: Prof. Sundeep Nayak, IAS (Retd.), is Professor of Practice and Chair, Mission LiFE Cell, IIT Goa. Dr. Kyawt Yin Min Thein is a former Researcher at CRDT, IIT Delhi, and Research Assistant, School of Planning and Architecture (SPA), New Delhi. Views are personal.

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