NITI Aayog has released a new report projecting that Artificial Intelligence (AI) could add between $500 and $600 billion to India’s GDP by 2035. AI for Viksit Bharat: The Opportunity for Accelerated Economic Growth positions AI as the key lever for India to achieve 8% annual growth.

The report incorporates analysis and insights from McKinsey & Company. This raises questions about whether the framing leans toward industry priorities rather than presenting a broader national perspective.

Furthermore, the report is not a Cabinet-approved policy and does not carry the weight of an official national strategy. It adds to a gap that stretches back to NITI’s 2018 AI strategy, which has seen little follow-up apart from the launch of the IndiaAI Mission in 2024.

How NITI Aayog Sees AI Driving Growth

Building on its growth projections, the report identifies three levers for AI-led value creation: accelerating adoption across industries, transforming research and development through generative AI, and expanding technology services exports. It focuses mainly on the first two, projecting that adoption alone could bridge up to 30–35% of India’s growth gap.

To begin with manufacturing, it proposes smart factory corridors, a national manufacturing data grid, AI-ready industrial parks, and shared 3D printing facilities. Meanwhile, financial services would rely on regulatory and innovation sandboxes, shared dashboards, fraud detection systems, and alternative data for credit decisions. In pharmaceuticals, the report expects progress through AI-enabled drug discovery, large-scale genome sequencing, and tiered access to research datasets.

Finally, in the automotive sector, it projects “software-assisted vehicles” reaching Level 3 autonomy by 2035, supported by testing parks, smart corridors, and anonymised vehicle telemetry.

The report also presents a vision of India as the “data capital of the world.” It highlights anonymised data frameworks, certified marketplaces with privacy tags, and sectoral data platforms as key measures. AI Kosh already hosts more than 350 datasets, and the report describes it as a foundation that can be scaled further.

On skills, the report proposes an AI Open University, national certification programmes such as “AI for Credit, Risk and Fraud,” and fellowships to embed AI experts in banks and regulators.

Ruchi Gupta, Executive Director of the Future of India Foundation, said the report departs from NITI’s earlier strategy. “The earlier report had a stronger public-interest framing, what AI can do for health, agriculture, education. This one is very industry-focused. This comes through from the Expert Council, which is dominated by industry. The lack of other perspectives makes this a bit lopsided,” she said.

Jobs and Productivity

Alongside growth projections, the report frames AI adoption as a way to unlock major productivity gains. However, concerns about its impact on employment remain significant. Gupta underlined that “there are legitimate anxieties about job displacement. All the IT majors are already letting people go, Tata Consultancy Services (TCS) is a recent example.”

The International Monetary Fund (IMF) estimates that generative AI exposes more than a quarter of India’s workforce, with 12% at high risk of displacement. Yet the report provides few answers beyond citing Singapore’s reskilling and transition models. Gupta argued that this approach falls short of India’s needs. “Singapore’s industry transition maps are an interesting example. The value add of the report would have been not in citing the example, which ChatGPT can also do, but in thinking through how they can be applied in the Indian context, with a surplus workforce and far less formalisation,” she said.

AI Policy Without Legislative Oversight

While the NITI Aayog report lays out ambitious sectoral roadmaps, official updates on AI policy continue to come mainly through Parliament’s Question Hour. On July 30, Electronics and Information Technology Minister Ashwini Vaishnaw responded to a starred question in the Lok Sabha on AI strategy. He highlighted measures under the IndiaAI Mission, including funding for four startups, Sarvam AI, Soket AI, Gnani AI, and Gan AI — to build open-source Indian foundation models, provisioning of 34,381 GPUs through the IndiaAI Compute Portal at subsidised rates, and expanding AI Kosh with more than 1,000 datasets and 208 models.

Additionally, the minister highlighted projects at the IndiaAI Safety Institute on bias mitigation, watermarking, machine unlearning, and deepfake detection. He said the government manages AI risks through existing frameworks such as the Information Technology Act, the Bharatiya Nyay Sanhita, the Digital Personal Data Protection Act, and the Information Technology Rules 2021. Notably, India still lacks a dedicated AI law.

Gupta’s article on the Future of India Foundation’s report Governing AI in India: Why Strategy Must Precede Mission highlights the scale of this gap. It found that between June 2019 and April 2025, fewer than 1% of Parliamentary questions in either House addressed AI. The Foundation’s report also noted that most sectoral committees have not engaged with AI, with the exception of the IT Standing Committee, which has acknowledged regulatory gaps.

Why It Matters

India has begun investing heavily in compute, datasets, and foundational models through the IndiaAI Mission, while presenting itself internationally as a leader in AI governance. Yet the absence of a Cabinet-approved strategy debated in Parliament leaves these initiatives without democratic legitimacy.

In her article, Gupta warned that without legislative engagement, India’s AI future risks becoming “technocratic, opaque, and vulnerable to elite capture.” Speaking to MediaNama, she added that what India needs now is a cohesive strategy and the government’s political heft to execute it. “For this, a Cabinet-endorsed national AI policy is imperative,” she said.

The NITI Aayog report adds another ambitious roadmap for growth. Moreover, it highlights once again the imbalance between executive-led initiatives and the representative oversight required to shape India’s AI governance.