IndiaAI Mission Progress Update
The Ministry of Electronics & IT submitted a comprehensive progress report on the IndiaAI Mission through Union Minister Ashwini Vaishnaw in Rajya Sabha on July 24, 2026. The mission, approved in March 2024 with an outlay of ₹10,371 crore over five years, aims to build a comprehensive AI ecosystem in India based on Prime Minister Narendra Modi's vision of democratizing technology while creating economic opportunities and employment for youth.
Mission Structure and Key Achievements
The IndiaAI Mission comprises seven pillars: IndiaAI Compute, Foundation Models, AIKosh, IndiaAI Application Development Initiative, FutureSkills, Startup Financing, and Safe & Trusted AI. Significant progress has been made across multiple areas, including support for 20 indigenous sovereign model proposals (12 LLMs and 8 SLMs) from Indian startups and institutions. Notable successes include Sarvam AI's 30 billion parameter and 105 billion parameter models, Gnani.AI's speech-to-speech model, BharatGen's multilingual foundation models, and Avataar AI's video generation model.
Compute infrastructure development shows 15 empaneled compute service providers supporting 237 projects with 93 lakh GPU hours sanctioned. Application development has seen 12 national-level hackathons/innovation challenges leading to 62 AI prototypes and 20 deployed AI solutions. Talent development initiatives have awarded 686 fellowships across undergraduate, postgraduate and doctoral programs in 178 institutions, while the YUVA AI for All program has been completed by over 26 lakh individuals.
Institutional Infrastructure Development
Twenty-seven India Data and AI Labs have been established, supporting training for more than 2,500 students, with work ongoing on an additional 188 labs. Fifty-eight Artificial Intelligence Centres of Excellence (AI-CoEs) are being established across States and Union Territories in collaboration with respective State/UT Governments and industry partners.
Safe & Trusted AI Initiatives
The Safe & Trusted AI pillar focuses on promoting responsible development, deployment and adoption of AI through indigenous governance frameworks, standards, tools and evaluation mechanisms. Thirteen Responsible AI projects have been approved in educational institutions across the country, addressing topics including bias mitigation, machine unlearning, privacy-preserving AI, explainability, deepfake detection and AI risk assessment.
Key initiatives include Saakshya, a multi-agent framework developed by IIT Jodhpur & IIT Madras for deepfake detection; AI Vishleshak for improving audio-visual forgery detection systems; and IIT Kharagpur's project on Real-Time Voice Deepfake Detection System. Specific domain projects include NIT Raipur developing responsible AI algorithms to reduce bias in medical image analysis and clinical decision-making, IIT Delhi (with IIIT Delhi and IIT Dharwad) developing privacy-preserving machine learning models using federated learning, and Defence Institute of Advanced Technology building explainable & privacy-preserving AI for security applications.
Governance and Global Engagement
The India AI Governance Guidelines establish a risk-based governance framework addressing algorithmic bias, misinformation, deepfakes and unintended societal harm, proposing institutional mechanisms including the AI Governance and Economic Group (AIGEG), Technology and Policy Expert Committee (TPEC) and AI Safety Institute (AISI) for oversight, standards and safety research. The IndiaAI Safety Institute, announced in January 2025, advances science-based indigenous research on AI safety and governance while overseeing implementation of projects under the Safe & Trusted AI pillar.
India actively engages with global AI governance processes including Global Partnership on Artificial Intelligence (GPAI), G20, and United Nations to ensure international norms reflect Global South perspectives. As Chair of the India AI Impact Summit 2026 in New Delhi, India contributed to shaping the global agenda through the New Delhi Frontier AI Impact Commitments (voluntary commitments by AI developers), Guidance Note on AI Governance, and Trusted AI Commons repository of open resources.