Tracking India’s AI push
Shafina Segon explains where higher education stands at the end of 2025 – and what 2026 must deliver
“The declaration of 2025 as the “Year of Artificial Intelligence” by the All India Council for Technical Education (AICTE) was more than a symbolic gesture¹. With more than 14,000 colleges and 40 million students within its ambit, Indian higher education operates at a scale few systems globally can match². Any coordinated shift at this level inevitably reshapes teaching, research, and academic culture.
As 2025 draws to a close, the question is no longer whether AI has entered Indian higher education – it clearly has. The more meaningful question is whether this adoption is translating into deeper research capability, stronger scholarly practices, and global credibility.
What has changed in 2025
The most visible shift has been institutional acceptance. AI tools are now being used across campuses for teaching support, assessment assistance, content development, and administrative workflows. Surveys indicate that a significant proportion of Indian higher education institutions have adopted generative AI in some form, particularly in teaching and learning processes³.
Equally important is the cultural shift. Institutions that were previously cautious or resistant are now experimenting. AI is no longer treated as a niche technology restricted to computer science departments; it is increasingly discussed across disciplines, including management, social sciences, and professional studies.
This openness matters. It creates space for experimentation and reduces the stigma around responsible use of emerging technologies.
What adoption does not yet mean
However, adoption should not be mistaken for maturity. Despite growing use of AI tools, India’s contribution to highly cited global AI research remains limited, accounting for less than 2% of top-cited publications in the field⁴. Research infrastructure – robust PhD pipelines, interdisciplinary labs, long-term funding mechanisms, and original dataset development – remains uneven and concentrated in a relatively small number of institutions.
India is earlier in this journey than some mature research systems – but unlike many, it has the scale, policy momentum, and institutional diversity to leap if it chooses depth over speed.
The distinction between using AI and producing knowledge with AI is critical. Without deliberate investment in research culture, AI risks becoming an efficiency layer rather than an intellectual accelerator.
A revealing shift in the wider AI narrative
Mainstream business and technology discourse reflects this tension. LinkedIn’s Big Ideas 2026 series, for example, highlights the emerging narrative of the “one-person unicorn” – ventures scaled by a single founder using AI systems to manage operations, design, finance, and decision-making⁷.
Whether such cases become common is less important than what the narrative reveals: a growing assumption that AI can compress organisational scale and reduce traditional institutional scaffolding. For higher education and research, this raises an uncomfortable parallel. If AI can collapse company size, it can also weaken academic safeguards – peer review, mentorship, deliberation, and institutional accountability – unless these are actively reinforced.
As barriers to creation fall, barriers to trust rise.
Ethics, integrity, and research culture
One of the clearest gaps exposed in 2025 is the limited integration of AI ethics and governance into academic curricula. A recent syllabus-level review found that only a small fraction of computing programmes in India include substantive, standalone instruction in AI ethics⁵. Where ethics is addressed, it is often peripheral rather than central.
This matters not only for teaching, but for publishing and research integrity. Institutions such as Banaras Hindu University have already documented ethical concerns and uneven guidance around AI use in academic research⁶. These are not isolated issues; they reflect broader systemic pressures.
Internationally, expectations around responsible AI and open science are becoming clearer, shaped by frameworks such as UNESCO’s recommendations on AI ethics and open science⁶. Research systems that fail to align with these norms risk reputational and scholarly isolation.
What 2026 must prioritise
If 2025 was about adoption, 2026 must be about capability.
First, India needs sustained investment in research infrastructure – not just skills training, but support for doctoral research, interdisciplinary collaboration, and original knowledge creation.
Second, AI ethics, data governance, and responsible research practices must move from optional discussions to core academic requirements.
Third, open-access publishing and open research infrastructure deserve greater institutional support. Reducing paywall dependence and strengthening transparent peer review are essential if Indian research is to gain visibility and trust globally.
Looking ahead
India’s AI moment in higher education is real, but it is unfinished. The choices made in 2026 will determine whether AI deepens research quality or merely accelerates existing weaknesses.
Leadership in AI is not measured by how quickly tools are adopted, but by how responsibly knowledge is produced, evaluated, and shared. On that measure, India has momentum – but also work to do.
References
- Times of India (2024). AICTE announces 2025 as ‘Year of Artificial Intelligence’.
- AICTE (2024). AICTE initiatives on Artificial Intelligence.
- EY–FICCI (2025). Harnessing AI in Higher Education. Ernst & Young India.
- Stanford Institute for Human-Centered AI (2024). AI Index Report.
- Arora, S. et al. (2025). AI Ethics Education in Indian Computer Science Curricula. arXiv.
- UNESCO (2021–2023). Recommendation on the Ethics of Artificial Intelligence; Recommendation on Open Science.
- LinkedIn News (2025). Big Ideas 2026: India Edition.
Shafina Segon is co-founder of Vikramshila Education and Aakashganga Open. She works closely with researchers and academic institutions on issues of research integrity, open access publishing, and the responsible use of technology in scholarly communication, with a particular focus on strengthening research culture in large and diverse systems.