The Union government has rolled out a major expansion of its artificial intelligence (AI) ecosystem, approving 58 AI Centres of Excellence and 543 Data and AI Labs across the country, even as the IndiaAI Mission has mapped 762 AI use cases across 62 ministries and departments.

The move, detailed by Union Minister of State (MoS) for Electronics and IT Jitin Prasada in a written reply in the Lok Sabha amid the Monsoon Session of Parliament, is intended to push AI-led governance, build talent in Tier-2 and Tier-3 cities and strengthen India’s position as a global AI hub.

IndiaAI Mission: 7 -pillar strategy for AI-led growth

At the core of this push is the ‘IndiaAI Mission,’ which is built on seven pillars:

  • AI compute
  • Indigenous foundation models,
  • Application development
  • Futureskills
  • Open datasets
  • Safe and trusted AI
  • Startup financing

The mission is anchored in Prime Minister Narendra Modi’s vision of “democratising technology”, with AI policy explicitly framed around creating economic opportunities and jobs for the youth while managing associated risks.

Under the IndiaAI Compute pillar, the government plans to create a high-end, scalable AI computing ecosystem to support startups and researchers. The Foundation Models pillar focuses on developing indigenous large language models, multimodal models and domain-specific small language models to ensure sovereign AI capabilities tuned to Indian languages and use cases.

Simultaneously, an IndiaAI Startup Financing pillar is meant to plug funding gaps across the startup lifecycle, from prototype to commercialisation, so that innovative AI solutions can be scaled rather than stalled due to capital constraints.

Centres of excellence and Data & AI labs: Building the AI backbone

A central plank of the government’s AI push is physical and institutional capacity. The Centre has approved a scheme to establish 58 Artificial Intelligence Centres of Excellence (AI-CoEs) across states and Union Territories, in partnership with state governments and industry.

These CoEs are intended to serve as regional hubs for advanced research, innovation and industry collaboration in AI. Under the approved framework, two AI-CoEs have been allocated for Tamil Nadu, reflecting the state’s existing digital and industrial base.

Complementing the CoEs, 543 Data & AI Labs have been approved under the IndiaAI FutureSkills pillar for ITIs and polytechnics in Tier-2 and Tier-3 cities. These labs are designed to provide training in AI, data annotation, data curation and applied data science, explicitly aimed at democratising AI education beyond metro cities. Of these, 18 labs have been allocated to Tamil Nadu.

The FutureSkills pillar also offers fellowships to undergraduate, postgraduate and doctoral students to support AI education and research. MoS Jitin Prasada said a total of 686 fellowships have been awarded nationally across 178 institutions, including 162 fellowships to students from Tamil Nadu (96 undergraduate, 34 postgraduate and 32 PhD).

ALSO READ

762 AI use cases identified across 62 ministries

To ensure AI is not confined to pilots and rhetoric, the IndiaAI Application Development Initiative (IADI) has been tasked with driving adoption in governance and public service delivery. Prasada informed Parliament that the IndiaAI Mission has already identified 762 AI use cases across 62 ministries and departments, following a structured exercise coordinated by the Cabinet Secretariat after the IndiaAI Impact Summit 2026.

Under IADI, a workshop on AI in public service delivery was held in April 2024, bringing together central and state government representatives. The workshop helped ministries and departments assess their data readiness, identify potential AI use cases and develop AI roadmaps for governance and public services through a “collaborative and consultative approach,” the minister said.

“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 added.

Innovation challenges: Taking AI from hackathons to deployment

The IndiaAI Mission is also using innovation challenges and hackathons to crowdsource and fast-track solutions for concrete problems. Under IADI, 11 national-level hackathons and innovation challenges have been launched across sectors such as healthcare, agriculture, governance, climate, cybersecurity and financial regulation.

The IndiaAI Innovation Challenge identified AI solutions in healthcare, agriculture, governance, learning disabilities and climate change. Thirty solutions were shortlisted in Stage 1 for pilot implementation with central ministries, states and public-sector entities, and five teams—one per sector—were selected for national-level deployment, with pilots currently underway in multiple states.

ALSO READ

The IndiaAI I4C CyberGuard AI Hackathon, run with the Indian Cyber Crime Coordination Centre (I4C), produced AI tools for classifying cybercrime complaints and identifying emerging crime patterns on the National Cyber Crime Reporting Portal; the shortlisted solution has been integrated into I4C’s systems.

Other targeted challenges include the IndiaAI–GSI Mineral Targeting Hackathon for AI-driven mineral prognostication, the CATCH (Cancer AI & Technology Challenge) with the National Cancer Grid to improve cancer screening and diagnostics, and the IndiaAI Face Authentication Challenge to strengthen exam integrity at UPSC through AI-based de-duplication and one-to-many photo verification. Solutions from Intelligent Document Processing and PMJAY Auto Adjudication challenges are being piloted to automate workflows and claims processing in public institutions.

Safe, trusted and governed AI: India’s techno-legal framework

The government has repeatedly stressed that its AI drive is tied to a “safe and trusted” AI framework rather than a laissez-faire approach. Under the Safe & Trusted AI pillar of the IndiaAI Mission, 13 Responsible AI projects have been selected across themes such as bias mitigation, algorithm auditing, explainable AI, privacy-preserving AI and deepfake detection, to develop indigenous tools and frameworks.

India has also notified the Digital Personal Data Protection (DPDP) Act, 2023, which provides a legal framework for processing personal data with provisions on purpose limitation, data minimisation, consent, and rights of access, correction and erasure. Significant Data Fiduciaries are required to appoint data auditors and undertake Data Protection Impact Assessments. In November 2025, the government released the IndiaAI Governance Guidelines, setting out a national framework for safe, inclusive and responsible AI development and deployment.

These guidelines envisaged institutional mechanisms such as an AI Governance and Economic Group (AIGEG) for strategic oversight, a Technology and Policy Expert Committee (TPEC) for technical and policy inputs, and an AI Safety Institute (AISI) to conduct safety research, testing and risk evaluation.

The IndiaAI Safety Institute—described in official communications as a “hub for indigenous research and development in AI safety”—is being established to support India’s technical and institutional capabilities for AI governance. It will work with academia, startups, industry and government to address risks like deepfakes, adversarial attacks and AI misuse, and develop standards, benchmarks and evaluation tools tailored to India’s socio-economic and cultural context.

CERT-In has issued advisories on adversarial AI threats, launched a Certified Security Professional in AI programme, and released guidelines on safe use of generative AI, complementing the broader governance framework.

Collaborative governance: From AI Impact Summit to ministry roadmaps

The IndiaAI Impact Summit 2026, held in New Delhi in February 2026, was a key moment in shaping the government’s whole-of-government AI strategy. At the summit, the Prime Minister urged ministries to engage actively with AI applications relevant to their domains and accelerate adoption in governance. Following this, the Cabinet Secretariat coordinated with ministries and departments to identify AI opportunities, which led to the 762 problem statements now mapped to use cases under the IndiaAI Mission.

The government points to these processes—workshops, consultations, hackathons, and challenge-based programmes—as evidence that states and ministries are being actively consulted and engaged in AI roadmap formulation rather than having solutions imposed top-down. The approved 58 AI Centres of Excellence, 543 Data & AI Labs, and hundreds of fellowships and pilots collectively represent the institutional hardware behind this strategy.

Taken together, the Centre’s decision to approve dozens of AI Centres of Excellence and hundreds of Data & AI Labs, along with a structured pipeline of use cases, innovation challenges and safety mechanisms, signals a clear intent: to embed AI across governance and the economy while building a domestic ecosystem of talent, startups, infrastructure and regulatory tools robust enough to make that transformation both scalable and safe.