Centre has approved 58 AI Centres of Excellence, 543 Data & AI Labs across India
New Delhi, July 29
The Centre has approved 58 AI Centres of Excellence and 543 data and AI labs across India and IndiaAI Mission has identified 762 AI use cases across 62 ministries, Union Minister of State for Electronics and Information Technology Jitin Prasada told Lok Sabha on Wednesday.
The Minister said in a written reply that under the IndiaAI Application Development Initiative (IADI), a workshop on AI in public service delivery was held in April which helped ministries and departments assess their data capabilities, identify potential AI use cases and develop AI roadmaps for governance and public service delivery through a collaborative and consultative approach.
"IADI has built a pipeline of AI solutions across priority sectors including healthcare, agriculture, governance, climate, cybersecurity and financial regulation, with pathways from ideation to pilot deployment and scale," he said.
The government has approved a scheme to establish 58 artificial intelligence centres of excellence (AI-CoEs) across states and union territories, in collaboration with the respective state/UT governments and industry partners. Under the approved framework, two AI-CoEs have been allocated for establishment in Tamil Nadu.
Apart from this, under the IndiaAI FutureSkills pillar, 543 Data & AI Labs have been approved for establishment across ITIs and polytechnics in Tier-2 and Tier-3 cities to provide training in AI, data annotation, data curation and applied data science. Of these, 18 Data & AI Labs have been allocated for establishment in Tamil Nadu.
Under the IndiaAI FutureSkills pillar, fellowships are offered to undergraduate, postgraduate and doctoral students to support education and research in artificial intelligence.
"A total of 686 fellowships have been awarded nationally across 178 institutions. Of these, 162 fellowships have been awarded to students from Tamil Nadu, comprising 96 undergraduate, 34 postgraduate and 32 PhD fellowships," the Minister said.
Additionally, an IndiaAI Safety Institute is being established as a hub for indigenous research and development in AI safety, aimed at strengthening India's technical and institutional capabilities for AI governance.
— ANI
Reader Comments
Finally, some concrete steps! 762 AI use cases across 62 ministries sounds promising. But I'm cautiously optimistic - many such grand announcements fizzle out. The pipeline from ideation to scale needs solid monitoring. Also, why only 18 labs in Tamil Nadu when we have so many ITIs? Should be more. Still, happy to see our government thinking about AI for public service delivery. Healthcare and agriculture AI use cases could be game-changers for rural India.
As someone who works in AI, this is impressive on paper. 686 fellowships seems modest for a country of 1.4 billion though. We need 10x that. And the Safety Institute - great idea, but India has no track record in AI regulation. We should learn from EU's AI Act rather than reinventing the wheel. Also, why no mention of quantum computing? AI and quantum go hand in hand. Still, a good start, let's hope it's not just politics.
This is a smart move. India has the talent pool but needs infrastructure. 543 labs in Tier-2/3 cities can democratize AI education. I work in tech in Bangalore and see the gap - even good engineers from smaller cities lack hands-on AI experience. If these labs are well-equipped with GPUs and real datasets, this could be transformative. Hopefully, the private sector partnerships are meaningful, not just names on paper.
Good intentions, but let's be realistic. Where will the trainers come from? Our education system still struggles with basic computer literacy in many areas. Data annotation is low-hanging fruit for jobs, but applied data science needs solid math backgrounds. Fellowships are great, but why only 686? Even Tamil Nadu alone needs thousands. And AI Safety Institute - to govern what? Without indigenous foundational models, we're just regulating foreign tech. Need to build our own models first. Overall, positive direction but execution is everything. 🤞