Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesiTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Nandan Nilekani’s case for an AI opportunity at Infosys is that businesses need more than AI tools: they need help integrating them into legacy systems, data, processes, governance, and day-to-day operations. At Infosys Investor AI Day in Bengaluru on February 17, 2026, the company’s chairman described AI as a change in how businesses operate—and argued that this creates work for IT services firms even as AI automates some tasks.
What Nilekani said at Infosys Investor AI Day
Nilekani spoke in a session titled “Tech transitions – Why is the AI transition different?” at Infosys Investor AI Day on February 17, 2026. He compared AI with earlier shifts such as the internet, smartphones, and cloud computing. In his view, those transitions often added a new technology layer or moved existing applications, while AI requires changes to business operations, customer journeys, architecture, talent, and operating models. He called it “a fundamental change in the way we do things.” The exchange-filed event transcript records his remarks.
His argument is not that every company will make the same changes, or that demand for IT services will rise automatically. It is that deploying AI across a large organization is difficult: older systems and technical debt can obstruct change, data may be fragmented, and businesses must address integration, reliability, security, governance, and organizational adaptation. A pilot that works in isolation is not the same as a system that can be trusted and operated at scale.
Recommended Free Tools
Nilekani also argued that AI tools could make some modernization work faster and more economical. That is his assessment, not a productivity result independently measured in the cited materials. He described the implementation challenge as a reason IT services companies could play a more critical role in the AI era.
#1 Best Overall
Where Infosys says the services work could be
In its February 17, 2026 announcement, Infosys organized its AI services strategy around six value pools. The list shows how the company frames the work surrounding enterprise adoption; it is not independent evidence that each area will produce a particular amount of revenue.
| Value pool | What it covers in the enterprise AI context |
|---|---|
| AI strategy and engineering | Planning and building AI capabilities suited to an organization’s goals and technical environment. |
| Data for AI | Preparing and organizing data so it can support AI systems. |
| Process AI | Applying AI to business processes, rather than treating it only as a standalone tool. |
| Agentic legacy modernization | Using AI agents in work to modernize older systems and applications. |
| Physical AI | AI applied in physical-world settings, rather than only in software workflows. |
| AI trust | Trust-related needs such as governance, reliability, and responsible deployment. |
Infosys co-founder and chairman Nilekani said, “While AI agents can automate tasks and enhance productivity, enterprises still require deep systems integration, governance, trust frameworks, and large-scale transformation capabilities to fundamentally re-engineer their businesses.” The statement is the company’s view of why services remain relevant as automation expands, not a guarantee of work or business outcomes for Infosys. The six-part framework and quotation appear in Infosys’ announcement.
What the market estimate does—and does not—mean
Infosys cited a recent Nasscom–McKinsey report estimating US$300–400 billion in incremental global AI-first services opportunity by 2030. That figure refers to a broader market estimate, not projected Infosys revenue, market share, or a company sales target. The reviewed materials do not give the estimate’s methodology, so it should not be treated as a precise forecast of realized spending.
Infosys also reported on February 17, 2026, that it was collaborating with 90% of its top 200 clients on AI journeys and had more than 4,600 AI projects underway. These are company-reported counts, not independently verified measures of completed deployments, customer results, or recurring revenue. The company’s release includes forward-looking statements; its strategy and reported activity should be distinguished from future performance.
The figures Nilekani used to describe the transition
At the February event, Nilekani contrasted the time he said it took the internet, smartphones, and AI to reach one billion users: more than 10 years, five years, and “a couple of years,” respectively. He also said many large companies spend 60–80% of their IT spending maintaining systems. These are his characterizations in the transcript; the cited materials do not provide an underlying measurement method or independent corroboration. They help explain his emphasis on the scale and accumulated complexity of enterprise change, but should not be read as a standardized comparison or a universal company statistic.
Why moving from AI pilots to deployment is hard
In his May 22, 2026 chairman’s message, Nilekani said companies can stall between AI pilots and scaled deployments because of legacy architecture, organizational inertia, data integrity, governance, and regulatory change. He emphasized that each business has its own context and undocumented dependencies, which can make modernization difficult. These are his and Infosys’ assessments, rather than findings from an independent survey in the cited documents.
He described the problem as a deployment gap: adding AI to existing structures may be insufficient if the underlying business processes, customer journeys, and operating models need redesign. In that message, he called this “root-and-branch surgery.” The phrase reflects his argument that enterprise AI adoption can involve operational transformation, not just software installation. The message is part of Infosys’ 2025–26 integrated annual report.
What is established—and what remains uncertain
The cited material establishes Infosys’ stated AI services framework, Nilekani’s rationale for why implementation and modernization matter, and the company’s reported client and project counts as of its February 2026 announcement. It does not establish how much of the broader market opportunity Infosys will capture, whether its AI work will be profitable, or how quickly enterprises will complete large-scale transformations.
Best Value
Nilekani reiterated the US$300–400 billion estimate and the 90% client figure in his June 23, 2026 annual general meeting speech. He also described an AI ecosystem that includes compute and cloud platforms, model developers, data and analytics providers, applications, and security technologies. That context reinforces that enterprise AI depends on a wider set of capabilities and providers; it does not establish a competitive ranking or comparative customer outcomes. His AGM speech is available from Infosys.
The practical takeaway is that Nilekani sees AI as shifting the focus of IT services toward execution: connecting AI to enterprise systems, improving the data and processes around it, and addressing trust and governance as organizations scale adoption. Infosys is positioning itself for that work, but the market estimate and company-reported activity do not by themselves prove future revenue or results.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
Quick wins for a faster PC:
Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →
