IndiaAI mission: Only 400 crore of the over Rs 10,000 crore 5-year outlay has been released

The Indian government's ambitious IndiaAI Mission, which aims to foster the growth of artificial intelligence (AI) in the country, has faced criticism over slow fund disbursement despite large allocations. The mission, which was launched with a five-year outlay of over Rs 10,000 crore, has only released a fraction of the approved budget so far. This development has raised concerns about the government's ability to operationalize the initiative at scale, particularly as global tech giants like Amazon and Microsoft are investing heavily in AI in India.

According to a recent Rajya Sabha reply by the Ministry of Electronics and Information Technology (MeitY), the government has released Rs 21.79 crore in the 2024-25 fiscal year against the revised estimates (RE) of Rs 173 crore, and Rs 379.15 crore in the 2025-26 fiscal year against the RE of Rs 800 crore, as of February 9, 2026. Notably, no funds have been released for the 2026-27 fiscal year against the budget estimate (BE) of Rs 1,000 crore.

The IndiaAI Mission's funds are distributed across seven key pillars: Compute Capacity, Foundation Models, Startup Financing, Safe & Trusted AI, Talent Development, Data Labs, and Overheads & Contingencies. The highest allocation has gone to Compute Capacity at Rs 4,563.36 crore, followed by Foundation Models at Rs 1,971.37 crore and Startup Financing at Rs 1,942.5 crore. In contrast, the Safe & Trusted AI pillar has been allocated only Rs 20.46 crore, which is about five times lower than the Rs 102.69 crore earmarked for overheads and contingencies.

Despite the slow fund releases, the government has reported some achievements under the IndiaAI Mission. It has onboarded more than 38,000 GPUs for a common compute facility accessible at subsidized rates, empanelled 14 AI service providers offering cloud-based GPU access, shortlisted 12 teams to develop indigenous foundational models or large language models, and approved 30 applications for India-specific AI use cases. The mission has also supported over 8,000 undergraduate students, 5,000 postgraduate students, and 500 PhD scholars for talent development. Additionally, 27 India Data and AI Labs have been established, with 543 more identified. The initiative has enabled access to compute resources for various entities, including academic researchers, startups, MSMEs, early-stage researchers, students, IndiaAI Fellows, and government entities.

The slow pace of fund releases raises questions about the government's capacity to scale the IndiaAI Mission effectively. This is particularly concerning given the emphasis on developing indigenous AI models. Meanwhile, global tech companies like Amazon and Microsoft are investing significantly in AI in India, which could further exacerbate the gap if the government's initiatives do not gain momentum. The slow progress in fund disbursement may also impact the mission's ability to achieve its goals, such as fostering talent development, establishing data labs, and supporting startups and research institutions.

In conclusion, while the IndiaAI Mission has made some strides in terms of achievements, the slow release of funds poses a significant challenge to its scalability and effectiveness. The government needs to address these concerns and accelerate the disbursement process to ensure the mission's success in building a robust AI ecosystem in India. This is crucial, especially as the country aims to stay competitive in the global AI race and leverage its potential in this rapidly evolving field.