60% of Indian HEIs now permit student use of AI tools, finds new survey
A new EY-FICCI survey of 30 leading higher education institutions (HEIs) in India shows AI is moving from trial to use at scale. Over 56% have formal AI policies in place, 60% allow students to use AI tools, and 53% use generative AI to create learning materials.
Institutions are also embedding AI into delivery and support: 40% use tutoring systems or chatbots, 39% use adaptive learning platforms, and 38% apply AI for automated grading. The study introduces a maturity model and a roadmap to help campuses progress from pilots to institution-wide adoption.
Where AI is being used now
- Generative AI for learning materials: 53%
- AI tutoring systems and chatbots: 40%
- Adaptive learning platforms: 39%
- Automated grading: 38%
- Plagiarism detection, curriculum design, and career guidance are rising use cases
Policy, data protection, and governance
The report flags a clear divide: classroom use is growing fast, while governance and data safeguards lag in places. Many tools rely on student submissions, engagement data, or biometrics-creating privacy and compliance exposure if handled poorly.
Institution-level controls are essential. Classroom policies should align to central safeguards, not replace them.
- Publish an institution-wide AI policy covering acceptable use, disclosure, and academic integrity
- Run vendor due diligence: data flows, storage location, retention, model training rights, and auditability
- Use central contracts with clear DPA/IT clauses; restrict shadow IT and unvetted plug-ins
- Set procedures for dataset quality, bias checks, incident response, and model output review
- Provide clear guidance to faculty on permitted use in teaching, assessment, and research
Curriculum: AI literacy for all, depth in STEM
The study recommends baseline AI literacy for every programme: core concepts, ethics, digital skills, critical thinking, and everyday applications. This reduces uneven student experience and supports fair assessment policies.
For STEM, integrate advanced topics such as machine learning, natural language processing, and robotics into core modules to build graduate capability that meets industry demand.
- Map programme learning outcomes to AI literacy outcomes (first-year common module works well)
- Embed responsible-use practices: citation of AI assistance, verification steps, and error-spotting
- Align assessment to higher-order skills: analysis, synthesis, critique, and applied projects
Faculty readiness and change enablement
Progress is uneven across capabilities and staff confidence. Institutions that invest in faculty development see faster, cleaner adoption.
- Offer short, practice-first workshops on prompt quality, evaluation, and classroom applications
- Create a faculty helpdesk and exemplar repository for assignments, rubrics, and course policies
- Incentivize pilots with small grants; share results across departments to speed diffusion
Move from pilots to institution-wide use
To quote Avantika Tomar of EY-Parthenon India: "To unlock the full potential of AI, India must move beyond experimentation to scale - by integrating AI tools across teaching and campus operations, embedding AI literacy across subjects, investing in digital infrastructure, and strengthening faculty capacity and governance frameworks."
- Prioritize use cases with measurable impact: student support, large-enrollment grading assist, and curriculum co-creation
- Integrate AI with LMS/SIS for sign-on, audit trails, and accessibility
- Track impact: learning outcomes, student satisfaction, time saved, and integrity incidents
- Close gaps in bandwidth, device access, and assistive tech to ensure equitable use
Assessment integrity without overreach
AI detection is imperfect and can create false positives. Focus on assessment design and transparent student expectations.
- Use process-based assessment: drafts, reflections, viva, and in-class components
- Require disclosure of AI assistance and the steps taken to verify accuracy
- Test applied skills with local datasets, novel prompts, and multi-step reasoning
90-day action plan for education leaders
- Publish an interim AI use policy for students and staff; include disclosure and integrity guidelines
- Stand up a cross-functional AI governance group (academics, IT, legal, QA, student reps)
- Audit current tools; whitelist approved options and disable risky ones
- Launch a campus-wide AI literacy primer; provide faculty micro-trainings with office hours
- Redesign two high-enrollment courses to include AI-supported learning and clear assessment rules
- Define metrics and a simple dashboard for outcomes, equity, and risk
Further reading and upskilling
- FICCI: Education initiatives
- EY-Parthenon: Strategy in education
- Complete AI Training: Courses by job role
Bottom line: AI use on Indian campuses is already substantial. The differentiator now is clear governance, faculty capability, and course design that rewards thinking over copy-paste.
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