Nandan Nilekani at Infosys AI Day 2026 | “AI Is a Fundamental Root-and-Branch Surgery”

Summary

In this keynote address, the speaker discusses the rapid evolution of AI and its profound implications for businesses. Highlighting the speed of AI adoption, the speaker emphasizes that this technological shift is more fundamental than previous transitions. Enterprises must modernize their legacy systems, reskill their workforce, and adapt to a non-deterministic world powered by AI. The talk explores the challenges of implementing AI at scale, bridging the deployment gap between technology advancement and business adoption, and the importance of strategic execution. The key message is that AI represents a massive opportunity, but businesses must manage the change effectively to succeed.

Takeaways

• 😀 AI transition is happening at a much faster pace than previous technological shifts like the internet and smartphones, thanks to existing infrastructure.
• 😀 Unlike previous tech changes, AI is not just a new layer; it’s a fundamental shift in how businesses operate, impacting both technology and business processes.
• 😀 The rapid pace of AI adoption is driven by the ubiquity of the internet and smartphones, enabling quick distribution of AI technologies.
• 😀 Legacy systems in enterprises must be modernized for AI to be effectively adopted. Many companies are burdened by outdated, siloed systems that prevent innovation.
• 😀 Businesses are increasingly shifting from 'buy' to 'build' AI solutions, as developing in-house applications has become easier and more cost-effective.
• 😀 A significant challenge enterprises face is the 'deployment gap'—while AI technology advances rapidly, businesses are struggling to implement it effectively.
• 😀 Talent transformation is essential; traditional roles like developers and QA testers are evolving into roles such as AI engineers, deployment engineers, and AI leads.
• 😀 Organizations must reskill their workforce and rethink their approach to hiring, training, and deploying talent to keep up with the demands of AI-driven change.
• 😀 First-principles thinking is crucial for implementing AI in business; companies must focus on core problems, not just on adopting tools.
• 😀 Enterprises need to address organizational and data silos and implement robust change management to successfully integrate AI into their operations.
• 😀 The opportunity for AI adoption is greater than ever, but the real risk lies in execution. Companies need a clear plan for how to implement AI at scale and speed.

Q & A

What makes this AI transition different from previous technological transitions?

This AI transition is unique because of its speed, reaching a billion users in just a couple of years, compared to previous transitions like the internet and smartphones, which took longer. Additionally, AI represents a fundamental shift in how businesses operate, rather than just an addition to existing systems.

Why has AI been able to spread so quickly compared to other technologies?

AI’s rapid adoption is largely due to the existing infrastructure from the previous technological eras, particularly the widespread availability of the internet and smartphones. These technologies have made it easier to distribute AI tools like ChatGPT or Gemini quickly.

What are some of the fundamental changes AI brings to business operations?

AI is not just a layer of technology; it changes the way businesses are structured and how they operate. Businesses need to rethink customer journeys, operations, and the overall business model to integrate AI into their processes, shifting away from traditional systems.

How will talent transformation be affected by AI?

Talent transformation will shift from traditional coding skills to a focus on orchestrating AI systems, managing non-deterministic outcomes, and addressing new challenges. This means that existing talent will need to be reskilled to adapt to new roles like AI engineers, forward deployment engineers, and AI leads.

What challenges do companies face when dealing with legacy systems?

Companies face significant challenges with legacy systems, including high maintenance costs, security vulnerabilities, and difficulties in innovation due to siloed data. Modernizing these systems is no longer optional if businesses want to fully benefit from AI.

What is the 'deployment gap' in AI implementation?

The deployment gap refers to the disconnect between the rapid progress in AI technology and the ability of businesses to deploy it effectively. While AI technology is advancing quickly, many businesses struggle with implementation due to organizational, data, and talent challenges.

How does AI’s speed of advancement impact business decision-making?

The fast pace of AI’s development forces businesses to make decisions quickly regarding technology choices. Businesses need to architect their systems in a way that can accommodate rapid change, as technologies today may already be outdated by tomorrow.

Why is modernization of legacy systems crucial for AI adoption?

Modernizing legacy systems is crucial because outdated systems drain financial resources and hinder innovation. AI adoption requires clean, integrated systems that are agile and secure, allowing companies to take advantage of AI tools efficiently.

What role does the shift from 'buy' to 'build' play in AI adoption?

The shift from buying pre-built software solutions to building custom systems in-house is becoming more prevalent due to AI’s ability to simplify development. Businesses are now more inclined to build their own AI-driven applications, which creates opportunities for service providers who can assist with building these systems.

How does AI change the way enterprises handle customer journeys and interfaces?

AI allows businesses to build 'agentic' interfaces that simplify customer interactions. These interfaces hide complexity behind AI systems, making them easier for customers to use, and can be customized based on specific customer journeys. Businesses will increasingly look to add AI layers to their existing applications.