When Prime Minister Narendra Modi addresses the India AI Impact Summit 2026 on February 19, the audience is expected to resemble a who’s who of global artificial intelligence. Rarely has New Delhi hosted such a dense concentration of technology power under one roof.
Among those scheduled to attend are Sundar Pichai of Google, Sam Altman of OpenAI, Jensen Huang of Nvidia, Dario Amodei of Anthropic, Demis Hassabis of Google DeepMind, Brad Smith of Microsoft, Alexandr Wang of Scale AI, and Cristiano Amon of Qualcomm.
The obvious question: why India, and why now?
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It’s about scale — and revenue
The short answer is business. As global tech firms pour hundreds of billions of dollars into developing and training advanced AI systems, they are under mounting pressure to convert that spending into predictable revenue streams.
There are only three mass-scale digital markets globally: the United States, China and India. China remains largely inaccessible to US AI majors due to regulatory and geopolitical constraints. That leaves India as the largest open frontier outside America itself.
India’s vast services economy — from IT and BPO to finance, education and consulting — represents fertile ground for AI deployment. If generative AI tools are most valuable in white-collar, process-driven environments, then a country often described as the “back office of the world” becomes a prime target market.
Enterprise, not just consumers
For companies like Anthropic and OpenAI, enterprise adoption is where the real money lies. Anthropic’s Claude models, for instance, are positioned for software development and workplace productivity use cases. With India housing one of the world’s largest IT services sectors, the potential customer base is enormous.
OpenAI has also been expanding its commercial footprint in India, while Google and Microsoft are increasingly pitching AI solutions to both private enterprises and public institutions. Recent collaborations in the education sector signal that AI deployment is no longer confined to experimental pilots but is moving toward mainstream integration.
Hardware players, too, see opportunity. India’s push for AI-focused data centres — supported by long-term policy incentives — presents a multi-decade demand story for chips, GPUs and high-performance computing infrastructure. For Nvidia and Qualcomm, India is not just a software market but a future hardware growth engine.
The data advantage
Beyond revenue, India offers something equally critical for AI development: scale of data.
With hundreds of millions of internet users and one of the world’s largest pools of AI engineers and developers, India provides a diverse, multilingual and real-world testing environment. For AI systems that must operate across languages, accents, economic contexts and regulatory environments, India functions as a stress test at population scale.
Industry analysts note that India now ranks among the top global contenders in AI competitiveness, not necessarily because it leads in foundational model creation, but because it excels in deployment at scale. That distinction matters. As AI moves from research labs to everyday workflows, large-scale adoption becomes as important as model innovation.
From back office to front office
For decades, India’s role in the global tech ecosystem was defined by outsourced services. The AI wave appears to be reshaping that narrative. Instead of merely implementing technology built elsewhere, India is positioning itself as a central arena where global AI systems are refined, customised and monetised.
The symbolism of Silicon Valley’s top executives flying to New Delhi underscores that shift. They are not here for optics alone. They are here because no global AI strategy can ignore India’s market size, talent base and policy momentum.
In the race to dominate artificial intelligence, winning the US is essential. But winning India may prove decisive.
About the author — Suvedita Nath is a science student with a growing interest in cybercrime and digital safety. She writes on online activity, cyber threats, and technology-driven risks. Her work focuses on clarity, accuracy, and public awareness.
