India Pushes Back at Davos: Why It Refuses to Be Called a ‘Second-Tier’ AI Power

“I don’t know what the IMF criteria has been, but Stanford places India at 3rd in the world for AI preparedness, in terms of AI penetration, and in terms of AI talent… All three - actually on AI talent it is number two. So I don’t think your classification in the second bouquet is right. It’s actually in the first.” - Ashwini Vaishnaw - IT Minister, India

At the World Economic Forum in Davos, Union Minister for Electronics and IT, Ashwini Vaishnaw, declared that India belongs in the "first group" of global AI powers. Challenging recent International Monetary Fund (IMF) rankings that placed India in a lower bracket, the Minister emphasized that India’s massive digital infrastructure and talent pool make it a leader, not a follower. 

Vaishnaw highlighted that India remains the world’s largest supplier of AI services and is rapidly building sovereign AI capabilities. This bold stance underscores India’s shift from being a back-office hub to a front-end innovator in the global Artificial Intelligence race

India’s growing role in artificial intelligence highlights the importance of mastering core AI skills such as machine learning, data analysis, and generative AI. Students and professionals enrolled in Data Science, Artificial Intelligence, and Generative AI courses can better understand how scalable AI systems are built, governed, and applied in real-world contexts.

India Counters IMF: The Argument for Tier-1 Status

During a high-level session at Davos, Minister Ashwini Vaishnaw contested the IMF’s classification of AI readiness. He argued that traditional metrics often overlook the sheer scale and speed of India’s digital transformation.

Why India Claims the Top Spot

• Global Service Provider: India continues to be the primary supplier of AI-related services to the world’s largest corporations, proving its foundational role in the global tech stack.
• The Talent Advantage: With the world’s largest pool of STEM graduates, India provides the human capital that drives global AI development at companies like Google, Microsoft, and NVIDIA.
• Sovereign AI Infrastructure: The government is actively investing in domestic compute power and indigenous "Linguistic Data Bank" projects to ensure AI benefits all 1.4 billion citizens.

The India AI Mission: Building a Tech-Sovereign Nation

The Minister detailed how the "India AI Mission" is strategically positioning the country to lead in Generative AI and ethical AI governance.

Strategic Pillars of Growth:

1. Compute Capacity: India is establishing a massive AI compute infrastructure, allowing startups and researchers access to high-end GPUs without relying solely on foreign clouds.
2. Data Democratization: By leveraging the India Stack, the government is making high-quality, non-personal data available to innovators to train "Made in India" models.
3. Skill Development: Large-scale initiatives are currently underway to upskill millions of Indian professionals, ensuring the workforce remains relevant as AI automates traditional roles.

India as the Global Benchmark for Ethical AI

Minister Vaishnaw also emphasized that India’s approach to AI is human-centric. While Western nations focus on commercial gain and others on surveillance, India is positioning itself as the voice of the "Global South" in AI ethics.

Leading the Global South:

India is advocating for AI regulations that protect democratic values while fostering innovation. By chairing international forums like the Global Partnership on Artificial Intelligence (GPAI), India is helping set the rules for how the world uses these transformative technologies.

Conclusion

Minister Ashwini Vaishnaw’s statements at Davos 2026 mark a turning point in India’s tech narrative. By rejecting modest rankings and asserting "Tier-1" status, India is signaling to the world that it will be a primary architect of the AI future. For the Indian workforce, this means the era of AI-led growth has officially arrived, offering unprecedented opportunities for those skilled in data science and machine learning.