"The hype levels are unprecedented… we need a reality check on AI," Infosys Co-founder Nandan Nilekani "One of the key differences between previous tech revolutions… is that for the first time, we intend to place trust in non-human intelligence for decision making. We are far more forgiving of human error, but much less forgiving of machine error. A few hundred thousand people die on the roads due to car accidents. And we take that as a given. But if one person is killed by an autonomous car, the provider of that has to go back to the drawing board for two years," Nilekani emphasised.

Artificial intelligence (AI) is having a moment—every headline screams disruption, every boardroom whispers about AI-first strategies. But Infosys co-founder Nandan Nilekani believes it's time for a reality check. "I thought today I'll briefly talk about, do a reality check on AI, because I think, you know, the hype levels are unprecedented," but he also believes that the hype and technology have always gone together.

AI evangelists promise the moon, but the path to building scalable, reliable, and inclusive AI systems is riddled with roadblocks—technical, cultural, infrastructural, and political.

"The reality is that we are facing challenges to build AI at scale and make it work for everyone."

Yes, large language models are impressive. Chatbots can summarise articles or write poetry. But scaling AI across enterprises, governments, and diverse user groups isn't just about writing good code—it's about building systems grounded in accountability and trust.

"Many public information on how products are getting delayed is taking much more time. It's much more complicated. Internal politics plays a part. So all the things that we know about institutions, individuals, egos—also applies to the world of AI," said Nilekani.

Why enterprise and government AI is so hard

Nilekani pointed out that consumer AI can afford to make mistakes. If a chatbot suggests the wrong dinner recipe, users might just let it go. But for enterprises, accuracy equals trust. "Enterprises have to make sure that they don't give wrong answers because enterprises are putting their brand behind an offering. And if that AI even has one or two percent error… that affects the brand itself."

He also addressed the structural barriers within government. Ministries and departments work in silos, data isn't easily shared, and decisions carry deep ethical weight. "Public sector has structural concerns. It has ministries, it has departments, everybody is territorial. So data is not shared. And if data is the lifeblood of AI, we have to find a way to bring all AI together, irrespective of which part of the government it comes from."

Nilekani further emphasised that AI isn't just another tech product. It's a shift in how we make decisions—entrusting non-human systems with human outcomes.

"One of the key differences between previous tech revolutions… is that for the first time, we intend to place trust in non-human intelligence for decision making." And that leap of faith is not an easy one. "We are far more forgiving of human error, but much less forgiving of machine error. A few hundred thousand people die on the roads due to car accidents. And we take that as a given. But if one person is killed by an autonomous car, the provider of that has to go back to the drawing board for two years," he emphasised.

India is at unique advantage

While the world debates how to make AI work at population scale, India has quietly built the foundation over the past decade—through its Digital Public Infrastructure (DPI). "Interestingly, this time around, while we expect AI adoption also to take 10–15 years, our belief is that in India it can happen much faster," noted Nilekani.

He reflected on how smartphones shifted from communication tools to transaction enablers thanks to this infrastructure: "When smartphones began… initial use of phones in India was communication and entertainment… But around 2015–16, with the rise of India's digital infrastructure… India's thing became more sophisticated and led to payments and transactions becoming a bigger part of the Internet world," said Nilekani.

This digital transformation birthed India's new-age digital giants—PhonePe, Meesho, PhysicsWallah, Urban Company, Zepto, Rapido—who leveraged DPI and a mobile-first population to scale rapidly.

AI for a billion Indians

To reach a billion users, Nilekani argued, India must break free from the English-language, touchscreen model.

"First, language will move from just Hindi and English to every major Indian language… Second, the UI from keyboard and touch will go to voice and video… Third, because of generative AI… you will go from static knowledge to dynamic contextual information that is at your fingertips at the time you need it."

In short, AI must listen in your language, answer intelligently, and do so affordably. "This will lead to India becoming the AI use capital of the world," Nilekani predicted.

Nandan Nilekani shared these insights during his keynote at the Carnegie India Global Tech Summit.