Imagine visiting two universities barely 300 kilometres apart.
At one campus, students build AI-generated films screened at national film festivals, finance students predict markets using AI simulations, faculty members create personalised learning journeys in minutes, and administrators use AI to improve institutional efficiency.
At the other, faculty are still attending introductory AI workshops, internet connectivity remains inconsistent, and classrooms continue to function much as they did five years ago.
Both institutions may describe themselves as “AI-enabled.” Only one is becoming AI-native.
That, perhaps, is the biggest finding emerging from ETEducation‘s first nationwide editorial study on Artificial Intelligence adoption across Indian higher education. Artificial Intelligence has become the most talked-about technology in education since the internet transformed classrooms two decades ago. Yet somewhere between government announcements, university press releases and AI product launches, an important question has remained largely unanswered — What is actually happening inside Indian classrooms?
As India prepares to celebrate AI Appreciation Day on July 16, ETEducation spoke with leading universities across the country to understand how deeply AI has penetrated teaching, learning, research and governance. The findings reveal a sector moving rapidly, but not uniformly.Some universities have redesigned entire academic ecosystems around AI, while others are still experimenting. Many are embracing the technology enthusiastically while simultaneously wrestling with ethics, governance and faculty preparedness. Perhaps most importantly, the meaning of being “AI-ready” is changing faster than institutions themselves.
Everyone claims to be “AI-enabled.” But how many campuses are genuinely AI-transformed? ETEducation’s first deep-dive into India’s AI readiness reveals a sector at a fascinating crossroads.
On paper, India’s higher education system appears to be marching confidently into the age of Artificial Intelligence. The National Education Policy (NEP) 2020 envisions AI literacy becoming foundational to education. The IndiaAI Mission is investing in building an AI-powered nation. Universities proudly announce Centres of Excellence, AI-powered classrooms, generative AI workshops, and industry collaborations. Across institutional websites, one phrase appears with remarkable consistency — AI-enabled campus.
Yet beneath the optimism lies a more complex story.
Because AI adoption cannot be measured by the number of ChatGPT subscriptions purchased, policy documents released, or courses introduced. It is measured by something far more difficult: whether AI is fundamentally changing the way students learn, faculty teach, research is conducted, and institutions operate.
That raises an uncomfortable but necessary question – How AI-ready are India’s universities—really? Let’s find out. The result is perhaps the most comprehensive snapshot yet of where Indian higher education actually stands in its AI journey. This is the first article in ETEducation’s special editorial series examining AI adoption across Indian education.
The AI readiness spectrum: One country, many stages of adoption
One of the strongest themes emerging from the responses is that there is no single model of AI adoption in Indian higher education. Instead, universities currently fall across a broad maturity spectrum.
At one end are institutions where AI has become institution-wide infrastructure.
JECRC University reports 100 percent student and faculty engagement with AI-enabled learning across approximately 25,000 students and nearly 1,800 faculty members. Rather than limiting AI to engineering programmes, the university has integrated AI into law, commerce, design, healthcare, media and management, supported through structured faculty development programmes and partnerships with major technology companies.
Similarly, Universal AI University has positioned itself as India’s first AI-native multidisciplinary university, embedding AI across management, psychology, liberal arts, music, design and future technologies rather than treating it as a specialised computer science discipline.
Amity University reflects another advanced model. More than 8,500 students enrolled in AI-related courses in the latest semester, while over 20 AI platforms are currently deployed across academic and administrative functions. Particularly notable is the dramatic growth in AI adoption among non-technical students—from just 335 enrolments in 2023-24 to more than 5,000 students today.
Meanwhile, institutions like NIIT University emphasise depth over scale. Having introduced AI-focused degree programmes nearly a decade ago, the university argues that true AI readiness is not about teaching students to use AI tools but preparing graduates capable of thinking critically beyond them.
Then there are specialised institutions taking an entirely different route.
The Indian Institute of Creative Technologies (IICT), operating under the Ministry of Information & Broadcasting, was conceived as an AI-native institution from inception. Here, AI is embedded directly into filmmaking, animation, visual storytelling and creative production pipelines rather than being retrofitted into legacy curricula.
Others, such as XLRI Delhi NCR, represent a more transitional stage. While widespread AI usage is visible among students and faculty, the institution is still formalising measurement mechanisms and institutional AI platforms, choosing first to focus on awareness, training and responsible adoption.
The contrast illustrates an important reality.
India’s AI transformation in higher education is not progressing uniformly. Instead, institutions are moving at very different speeds depending on their legacy systems, academic focus, resources and strategic priorities.
If policy tells one story, classrooms tell another. Almost every institution described AI as fundamentally altering the teaching-learning process, not by replacing faculty, but by changing where human effort is invested.
India’s AI Adoption Across Campuses
At NIIT University, students now spend less time searching for information and debugging code, allowing classrooms to prioritise critical thinking, experimentation and design thinking. Faculty members increasingly use AI to create case studies, assessments, personalised learning materials and quicker feedback.
XLRI faculty describe generative AI as dramatically reducing the time needed to create customised classroom content. Instead of manually redesigning lectures for different learner groups, faculty can rapidly iterate teaching material while retaining academic judgement over quality.
While, Amity University reports improved student participation through AI-assisted lesson planning and personalised learning support. Universal AI University focuses less on tool usage and more on AI-enabled collaborative problem-solving, where multidisciplinary student teams tackle real-world business challenges using AI-supported simulations.
IICT provides perhaps the most compelling demonstration of experiential learning. Rather than stopping at classroom exercises, students contribute to production-quality national projects—including films showcased at the Mumbai International Film Festival and projects for the Indian Air Force and National Film Development Corporation.
Collectively, these examples point towards a broader educational transformation.
The classroom is moving away from information delivery towards judgement, creativity, questioning and applied problem-solving. As one institutional leader aptly observed, AI is allowing students to spend less time searching for answers, and more time learning how to ask better questions.
By the Numbers:
Policy is moving faster than infrastructure
Almost every institution acknowledged that NEP 2020 has significantly accelerated AI integration.Among the policy recommendations viewed as most successfully implemented are:
- AI integration into mainstream curriculum
- Multidisciplinary learning
- Skill-based education
- Industry partnerships
- Credit-based AI programmes
- Experiential learning
These reforms are already visible across campuses. However, translating policy into classroom reality remains uneven. Several recurring implementation challenges emerged.
1. Faculty readiness: Universities consistently identified faculty capability as the single biggest determinant of AI success. Technology evolves every few months. Faculty development cannot remain a one-time workshop. Instead, institutions increasingly view continuous reskilling as essential.
IICT’s Train-the-Trainer programmes and JECRC’s structured faculty development initiatives illustrate how institutions are attempting to address this challenge.
2. Responsible AI governance: Interestingly, even institutions leading AI adoption admitted that governance remains their biggest unresolved issue. Questions surrounding academic integrity, AI-assisted assessments, plagiarism, ethical usage, bias, privacy and accountability remain works in progress.
Universal AI University describes responsible AI governance as the next frontier. JECRC similarly notes that institutionalising ethical AI across large and diverse student communities remains significantly more challenging than introducing AI tools.
3. Digital Inequality: Perhaps the most sobering concern relates to access. While elite universities rapidly expand AI ecosystems, many institutions across India continue to struggle with basic digital infrastructure. Reliable internet connectivity, computing devices and digitally trained teachers remain prerequisites before AI can meaningfully reach classrooms.
As several institutional leaders cautioned, without addressing these structural gaps, AI risks widening educational inequality instead of reducing it. The divide may no longer simply be between public and private institutions. Increasingly, it could become the divide between AI-rich campuses and AI-poor campuses.
The new competitive advantage: AI culture, not AI software
One message emerged repeatedly across almost every conversation. Buying AI tools is easy, building an AI culture is considerably harder.
Institutions that appear furthest ahead are not necessarily those deploying the largest number of platforms. Rather, they are redesigning curriculum, assessment, faculty development, interdisciplinary learning, research practices and industry engagement around AI.
As one university leader remarked, “A login count tells you nothing; a curriculum redesign tells you everything.” That observation perhaps captures the current moment better than any adoption statistic.
Where Indian higher education stands today?
Taken together, the findings paint a nuanced picture. Indian higher education has clearly moved beyond AI experimentation. Across leading institutions, AI has entered classrooms, administrative offices, laboratories, creative studios and research environments. Faculty are increasingly becoming AI users, students are moving beyond AI awareness towards AI-assisted learning. Infact, curricula are expanding across disciplines, industry collaborations are strengthening.
Yet the transformation remains incomplete, due to:
- Responsible governance frameworks remain immature.
- Assessment models are still evolving.
- Faculty readiness varies widely.
- Infrastructure gaps continue to shape institutional capacity.
- Most importantly, the definition of AI readiness itself is changing.
AI Campus Snapshot 2026
The future will not belong to universities that merely introduce AI courses. It will belong to institutions capable of cultivating critical thinkers who understand when to trust AI, when to challenge it, and when to think beyond it.
As India’s higher education ecosystem enters the next phase of AI adoption, the conversation is shifting from “Who has AI?” to a far more meaningful question – Who knows how to build an education system where humans and AI learn together, and responsibly?
This is the first story in ETEducation’s special editorial series examining Artificial Intelligence across Indian education. The next story will explore how the investment in AI has created real impact? Stay tuned!
