India’s AI push in HE hits faculty, researcher shortage

India’s US$77 million push to build the country’s first Quantum and AI University in Amaravati in the southern Indian state of Andhra Pradesh is ambitious.

The blueprints are aspirational, but they hit an immediate bottleneck: India has a massive shortage of qualified AI professors and researchers.

The National Institute of Electronics & Information Technology (NIELIT), operating under India’s Ministry of Electronics & IT, has signed a Memorandum of Understanding with the Andhra Pradesh government to establish the campus.

But as India pours millions into cutting-edge AI infrastructure, it faces a fundamental constraint: world-class facilities can be built relatively quickly, but the highly skilled faculty needed to teach, conduct research and train the next generation of AI talent cannot be created overnight.

Dr Pankaj Mittal, secretary general, Association of Indian Universities, told University World News: “India needs many more qualified AI faculty to support the scale and speed at which AI is expanding.

India has a growing pool of capable faculty in computer science, data science, mathematics, statistics, machine learning and related disciplines, but the number of academics with deep, specialised expertise in advanced AI is still limited.”

The Stanford AI Index Report, prepared by the Stanford Institute for Human-Centered AI or HAI, tracks the global concentration of AI talent using LinkedIn data.

The report indicates that India accounts for nearly 15% to 16% of the global AI workforce. But its contribution to high-quality AI research stands at only around 2%.

NITI Aayog’s 2025 AI roadmap identifies talent retention as a major challenge; this is because many top AI experts prefer working for high-paying technology companies or moving abroad rather than joining universities.

Consequently, premier institutions like the Indian Institutes of Technology (IITs) struggle to recruit and retain skilled faculty members, according to a former IIT Delhi Professor, V Ramgopal Rao.

Vast disparity in salaries

A primary reason for this issue is the vast disparity in salaries. Technology companies and private research labs often offer AI professionals salaries substantially higher than those at public higher education institutions, which are bound by fixed government pay structures.

NITI Aayog has identified this pay gap as a factor pushing PhD graduates towards private-sector opportunities in India and abroad.
In addition, advanced AI research requires powerful computers, large GPU clusters, and high-quality datasets. While these resources are readily available in private companies, most Indian universities lack them, said Mittal.

According to Rahul Choudaha, principal of DrEducation Research – an observatory of global higher education trends and insights: “Even before the AI boom, India has been facing a persistent challenge of attracting talent into academic and research tracks even for some of the leading institutions like the IITs (Indian Institutes of Technology) and IIMs (Indian Institutes of Management).”

He said one major reason is that top talent commands far higher compensation in industry than in
faculty roles.

“Another way to look at it: cutting-edge research on topics like AI isn't really happening in underfunded universities – it’s happening in the labs of well-funded companies and even startups.

“For someone in a fast-moving, high-growth field like AI, the opportunity to learn and contribute is simply much greater in industry,” Choudaha told University World News.

Although initiatives such as the Prime Minister Research Fellowship (PMRF) and the IndiaAI Fellowship are providing financial support for doctoral and AI research, India still faces a weak research pipeline.

The IndiaAI Fellowship provides PhD scholars with monthly financial support and research grants, while PMRF offers similar support for doctoral researchers.

NITI Aayog, however, says India produces fewer than 500 AI-related PhDs annually and that nearly 44% of the country’s top AI researchers work abroad, citing better-funded laboratories and clearer career paths.

NITI Aayog also says government pay scales in emerging high-skill sectors such as AI are less attractive than private-sector opportunities, leading many PhD graduates to pursue jobs in the private sector in India and abroad.

Mittal said universities face additional constraints because recruitment and promotion processes can sometimes be slow and rigid.

“An outstanding AI researcher may not fit neatly into conventional academic disciplines or evaluation systems. Similarly, traditional measures of academic performance may not fully recognise open-source contributions, patents, AI models, datasets, industry collaboration, technology transfer or entrepreneurial activity.”

Rapid expansion without qualified faculty

The rapid expansion of AI programmes is creating another challenge: universities must compete for a limited pool of experienced AI researchers and faculty.

A higher-education brief by Wiley and NVIDIA notes a global shortage of AI talent and says universities need competitive research environments to attract and retain qualified faculty.

An IIT faculty member said the rapid expansion of AI programmes could put additional pressure on institutions that are already struggling to recruit specialised faculty and build the research infrastructure needed to support them.

New AI institutes may expand rapidly without having enough qualified teachers or adequate research facilities. There is a global shortage of experienced AI professors and researchers; consequently, many higher education institutions are forced to hire less experienced teachers to meet the growing demand.

At the same time, a large number of students wish to study AI, placing pressure on universities to increase admissions and expand their programmes – even though they often lack the adequate faculty, labs, and infrastructure to deliver high-quality education.

To address these challenges, leading IITs have established dedicated AI schools and research centres – such as the Yardi School of AI at IIT Delhi and the School of Data Science and AI at IIT Madras.

They are also appointing faculty fellows and ‘Professors of Practice’, enabling experienced industry professionals to teach and lead research without leaving their corporate jobs. While these measures are helpful, long-term solutions are still needed to strengthen AI education and research in India.

India will need more than 1.25 million AI professionals by 2027, up from an estimated 600,000–650,000 in 2024, according to NASSCOM, the National Association of Software and Services Companies, which represents more than 3,000 tech companies.

Mittal said: “India needs a stronger AI research pipeline, including flexible interdisciplinary faculty positions, competitive research packages and expanded PhD and postdoctoral programmes.”

Universities should also partner with industry through joint appointments and collaborative research, she said, while regulators should allow greater flexibility in recruitment, compensation and faculty workloads without compromising academic standards.

US, China retain more AI talent

Choudaha said India’s AI faculty bottleneck is closely linked to its difficulty in competing with the United States, China and other major AI hubs for research talent.

“Compensation and career-track competitiveness against industry and foreign academia remain central challenges,” he said.

India also faces a gap in research infrastructure, particularly access to computing power and well-funded laboratories, compared with what leading US and Chinese institutions can offer.

Bureaucratic delays in recruitment, especially in public universities, further compound the problem in a field where demand for talent is rising rapidly.

Choudaha said migration was another important factor. Many research-orientated Indian students pursue masters degrees and PhDs abroad and remain overseas, while researchers who begin their careers in India may later move abroad for postdoctoral and research opportunities.

“India is a source country for AI talent, but not yet a strong retention destination for its own talent,” he said, citing the MacroPolo Global AI Talent Tracker.

The challenge is different in the United States, where universities have a stronger research and faculty pipeline but face intense competition from technology companies for top AI researchers.

China, meanwhile, has invested heavily in expanding AI education and research capacity and has been more successful in retaining a large share of its domestic research talent.

The United Kingdom also faces an AI skills shortage, but universities and industry increasingly use partnerships, flexible appointments and competitive research opportunities to attract specialists.

Faculty development is key

India’s rapidly expanding AI programmes could therefore intensify competition for a relatively limited pool of researchers unless faculty development and retention receive equal attention.

“Dedicated AI universities can strengthen the pipeline over time, but they will also intensify competition for a limited pool of highly qualified faculty in the short term,” Choudaha said.

India needs a more proactive strategy combining competitive research funding, international recruitment, diaspora engagement and stronger academic-industry links.

Mittal called for a “quality before scale” approach, with new AI institutions developed alongside clear benchmarks for faculty quality, research output, PhD supervision and infrastructure.

The priority, she said, should not simply be to produce more AI graduates but to build the academic capacity to produce the next generation of AI knowledge and talent.

This requires a national ecosystem linking undergraduate and postgraduate education, doctoral and postdoctoral research, faculty development, industry partnerships, international collaboration and shared research infrastructure, she added.