Nasscom 2026 Leadership Summit : Cobol’s AI moment, Nasscom says legacy tech debt can fuel India’s next services surge

The Nasscom Technology & Leadership Forum 2026 opened with a familiar feeling in the room: everything is changing, and at a rapid pace. The nexus of forces—from AI to quantum to the very relevance of IT services as we know it today—is at an inflection point. These forces are not arriving in neatly packaged forms, but in many shapes and sizes. Adding another layer of complexity, they are converging, colliding and landing inside boardroom priorities in real time.

Rajesh Nambiar, President, Nasscom, set the tone with a leadership challenge that felt more practical than aspirational. In an age of exponential change, leadership is about sensemaking: connecting the dots between technology, trust and transformation, without chasing every new wave for its own sake.

This summation mattered because the questions it leads to are already on every CXO’s agenda. What happens to jobs. Whether the IT services model stays relevant. What Nasscom must do as member companies reset strategies, talent and delivery models.

2025 was not a soft transition. It was a leap

Sindhu Gangadharan, Chairperson, Nasscom, described 2025 as a year when faster AI adoption was expected, but the pace still surprised organisations. Complexity rose alongside adoption. Geopolitics, she noted, has also become a constant presence in business conversations, shaping how leaders think about resilience, trust and long-term viability.

Her most telling point was about how quickly work itself has shifted. The move, she said, has been from writing code to orchestrating intelligence. Not slowly, not gradually, but over weeks and months as tools and models improved.

In that environment, she argued, the winners will be those who can keep moving fast without breaking trust.

Success will be defined by how you balance trust with agility.” — Sindhu Gangadharan

Cobol’s AI moment: the unglamorous opportunity with huge upside

The most relatable insight of the session came from the inner soul of enterprise IT, deeply submerged in disruptive tech, yet the most important transformation tech stakeholder – its legacy systems and its modernisation. The age old probelm child in enterprise IT.

Reflecting on this, Srikanth Velamakanni, Vice Chairperson, Nasscom, pointed to Cobol modernisation as a real, near-term opportunity that can reshape the economics of enterprise transformation. Across banking, insurance, government and large enterprises, Cobol-based systems still run critical processes. They also represent deep technical debt that organisations have known they must address, yet often postpone because the risks feel career-ending and the budgets feel unmanageable.

Giving a sense of the impending opportunity, Velamakanni says, " With 800 billion lines of Cobol code in play, even $2 a line translates into a $1.6 trillion tech services opportunity. That is tech debt turning into an expanded TAM.”

Velamakanni’s argument was that AI changes that equation. Better accuracy and AI-assisted coding can lower the cost of modernisation and reduce uncertainty, making projects that once looked too risky and too expensive far more feasible.

His wider conclusion was clear: this does not shrink the services market. It expands it by unlocking work that has been deferred for years.  “This is an expansion of TAM, not the other way around, " says Velamakanni

The significance is not just about cost reduction. It is about confidence. When the price and delivery risk come down, boards fund projects that were previously “known problems” but never actioned. That is where legacy clean-up turns into growth.

From assistance to autonomy: why delivery models are shifting

The session also underlined a broader shift underway in software delivery. AI is moving beyond being a productivity helper to becoming a system that can produce more output with less hand-holding, especially in coding.

Velamakanni described a fast-changing environment in which organisations move from using AI to assist developers to relying on AI-generated code for larger parts of engineering workflows. That transition forces the industry to rethink what services look like, how outcomes are measured, and how value is priced.

In this view, the old metric of “how many people can we deploy” gives way to a sharper question: “how quickly can we modernise, re-architect and deliver outcomes safely”.

Enterprise adoption is uneven, but use cases are breaking through

Gangadharan offered a grounded reality check. Enterprise penetration of AI is still uneven, and there remains a real gap between experimentation and production-grade deployment.

Even so, she pointed to use cases emerging across sectors, including regulatory and trade intelligence, predictive maintenance in asset-heavy environments, faster workflows in healthcare diagnostics, and complex decision-making in pharmaceuticals where compliance, substitutions and delivery constraints must be handled without breaking rules.

Her emphasis was consistent: data integrity, governance and responsible deployment are the foundations that turn AI promise into operational value.

What humans do next: the talent reset is already underway

The human question surfaced repeatedly, as it does in every serious AI discussion. If AI can modernise systems faster, write more code, and automate more workflows, what changes for people?

Velamakanni advanced three priorities enterprises must confront: reimagining business processes, building an intelligence layer on top of enterprise data, and reshaping the workforce through upskilling and reskilling.

He also suggested hiring patterns may tilt towards people who combine high talent with less conventional experience, especially those who think in AI-native ways and are not anchored to legacy habits.

Gangadharan reinforced the need for member companies to build AI-first skills while creating the mindset and governance needed to deploy systems responsibly.

What Nasscom is signalling for 2026

For Nasscom, the opening message was not simply about excitement around new models. It was about what it takes to convert acceleration into durable advantage.

That includes guiding member companies through AI-led services delivery, business model shifts, and workforce transitions, while keeping trust and resilience central.

But the deeper message of the session may be the most useful one for enterprise leaders in India right now: the next big wave is not only about building new things. It is also about finally fixing the old things that still run the world, and doing it at a pace and cost that makes transformation possible.