Ashwini Vaishnav Rejects IMF AI Ranking at Davos, Says India Is Among Global AI Leaders

Union Minister Ashwini Vaishnav strongly objected to the International Monetary Fund’s (IMF) AI readiness ranking during a discussion at the World Economic Forum in Davos, Switzerland. The ranking, released by the IMF’s Managing Director, categorised countries into three groups: global AI leaders driving change, nations observing the transformation, and those largely disconnected from it.

In the index, the United States, Denmark, and Singapore were placed in the top category. India, despite recognition of its rising investments in information technology and digital infrastructure, was placed in the second group alongside emerging economies such as Saudi Arabia. This classification did not sit well with the Indian minister.

“India belongs in the first line of AI leaders”

When asked whether India needs closer coordination with countries like the US and China to move into the top tier, Vaishnav outright rejected the premise of the ranking. Speaking firmly from the Davos stage, he said India should not be underestimated and clearly belongs among the world’s leading AI nations, not in a secondary category.

He stressed that India is building a comprehensive and future-ready AI ecosystem and is already competing with the best globally across the entire AI value chain.

Explaining India’s AI strength: the five-layer framework

Ashwini Vaishnav explained that artificial intelligence rests on five critical layers, and India is actively working across all of them.

Application layer – delivering AI at population scale

This is the layer closest to citizens and industry. India’s strategy focuses on deploying AI at a massive scale to create real-world impact. AI-driven solutions are already influencing agriculture, healthcare, education, manufacturing, and governance. According to Vaishnav, value in AI comes not just from innovation, but from widespread adoption.

Model layer – the intelligence behind AI

This layer focuses on AI models that enable decision-making. While frontier AI models have demonstrated immense potential, they are capital- and compute-intensive. India is encouraging open-source models to lower costs and barriers, while also developing localised models tailored to Indian languages, sectors, and regulatory needs. Vaishnav highlighted the importance of sovereign AI models to ensure data security, cultural relevance, and strategic autonomy.

Chip and compute layer – powering AI systems

AI depends heavily on advanced computing hardware such as GPUs, TPUs, and NPUs. The minister noted that affordable and accessible computing is crucial for startups, researchers, and innovation. Under India’s national AI mission, subsidised GPU access has been provided—over 38,000 GPUs at nearly one-third of global average costs. India is also investing in semiconductor fabrication units and advanced chip packaging to strengthen domestic capabilities.

Data centre layer – the digital backbone

Data centres host AI models, data, and computing power. Vaishnav pointed out that India has seen massive investments in this area, with companies such as Google, Microsoft, and Amazon collectively investing around $70 billion. Ongoing innovation is improving cooling efficiency, water usage, and energy management, while also boosting digital sovereignty and creating high-value jobs.

Energy layer – sustaining AI at scale

Reliable, round-the-clock power is essential for AI infrastructure. As AI workloads grow, energy demand rises sharply. While renewable energy plays a key role, it remains intermittent for 24×7 operations. Vaishnav highlighted nuclear energy as a clean and stable solution, referencing the SHANTI Act, which proposes nuclear-powered AI infrastructure through small modular and micro reactors, supported by public–private partnerships and foreign investment.