Government widens AI skills network beyond major cities

The government has approved 543 Data and Artificial Intelligence Labs in industrial training institutes and polytechnics, alongside 58 AI Centres of Excellence, as it seeks to expand advanced technology skills and research capacity beyond the country’s largest urban centres.

The laboratories will be established across Tier-2 and Tier-3 cities under the IndiaAI FutureSkills programme. They are intended to provide practical training in artificial intelligence, data annotation, data curation and applied data science, giving students in technical institutions access to infrastructure and courses aligned with emerging employment needs.

The 58 Centres of Excellence will be developed across states and Union Territories through partnerships involving state administrations, academic institutions and industry. Their mandate is expected to include research, product development, startup support, workforce training and the application of AI to local economic and public-service challenges.

The expansion forms part of the ₹10,372 crore IndiaAI Mission approved in March 2024. The programme is structured around seven areas covering computing capacity, indigenous foundation models, application development, skills, datasets, startup financing and safe deployment of artificial intelligence.

Twenty-seven Data and AI Labs have already been established with the National Institute of Electronics and Information Technology in Tier-2 and Tier-3 locations. The additional 543 facilities will take the planned national network to 570 laboratories, extending the initiative through ITIs and polytechnics in all states and Union Territories.

Courses are being designed to offer both foundational instruction and sector-focused training. Planned subjects include data cleaning, Python-based annotation and curation, data science, generative AI awareness and the responsible use of automated tools. The laboratories are also expected to provide hands-on access to computing systems rather than relying solely on classroom theory.

The programme addresses a persistent concentration of technology education, research institutions and high-value digital employment in major cities. Students in smaller industrial and educational centres often face limited access to specialised trainers, computing infrastructure and industry networks, even as companies seek workers capable of handling data-intensive operations and AI-supported processes.

Industrial training institutes and polytechnics have been chosen because of their role in preparing students for technical occupations. Integrating AI modules into these institutions could connect traditional vocational education with changing requirements in manufacturing, logistics, healthcare, agriculture, retail, financial services and public administration.

The government is also developing standardised curricula for different levels of technical ability. The YUVA AI for All programme supports introductory literacy, while the Skilling for AI Readiness framework offers nationally aligned learning pathways for school students, educators, technical trainees and workers without formal computing backgrounds.

More than 120 AI-related courses are available through the Skill India Digital Hub, including 11 focused specifically on generative artificial intelligence. A 15-hour course titled AI to be Aware introduces learners to generative tools, practical applications, limitations and responsible usage under the National Skills Qualification Framework.

The laboratory rollout is being accompanied by a wider effort to strengthen research and deployment. The IndiaAI Mission has identified 762 potential AI use cases across 62 ministries, covering areas such as healthcare, agriculture, climate management, cybersecurity, financial regulation and government service delivery.

Eleven national hackathons and innovation challenges have been launched to move selected ideas from initial development towards pilot projects and wider implementation. The government has also approved applications for AI solutions designed around domestic languages, datasets and operational conditions.

The common computing programme has onboarded more than 38,000 graphics processing units, which are being offered to startups, researchers and academic institutions at subsidised rates. Access to such computing power is essential for training and testing large models, but costs remain a barrier for smaller companies and institutions.

Twelve organisations and consortia have been selected to develop large and small language models using domestic datasets. Participants include startups, technology companies and academic groups working on multilingual, multimodal and sector-specific systems. The resulting models are expected to support government applications and become available to the broader research and startup ecosystem.

Talent development under the mission includes support for more than 8,000 undergraduate students, 5,000 postgraduate students and 500 doctoral researchers. The laboratory network is designed to widen the entry point further by reaching students enrolled in vocational and diploma-level programmes.

Implementation will depend on the availability of qualified instructors, reliable connectivity, maintained hardware and sustained coordination between institutions and industry. Training outcomes will also need to be measured against employment, certification and practical competence rather than the number of laboratories formally approved.