As the global AI race fragments into blocs—the US doubling down on frontier models and chips, China building sovereign capacity at scale, and Europe tightening regulation—Indian technology leaders are asking an urgent question: where exactly should India play?
India’s opportunity may not lie in building the next foundation model. Instead, it may excel in something less glamorous, and potentially more durable: software capability, enterprise process knowledge, and talent at scale.
“Melting Pot” of Enterprise AI
During a panel discussion on ‘India’s Moment—Reinventing the Services-as-Software Operating System for Global Enterprise’ at the HFS India Summit 2026, Lalit Ahuja, Founder and CEO, ANSR Inc, which helps organisations manage and scale global capability centres (GCCs) in India, argued that India’s role will be less about invention at the frontier and more about making AI work inside enterprises.
He described India as “the melting pot of people, change management, target operating models, use cases—just the raw capacity that would be needed to bring about the benefits of AI to the enterprises.”
In his view, GCCs are already stepping into that role. AI, he said, is “going to be the biggest change management imperative businesses have ever seen,” and GCCs, by nature of their form and structure and construct, will offer the opportunity to lead the change management across the enterprises.”
The implication is structural: AI will force companies to reimagine work.
Can’t Win Every Layer
Arindam Mukhopadhyay, Managing Director and GBS Head, Citi, contexualised Indian ambitions within the broader AI stack—from infrastructure and power to models, software, and services. With India’s massive population its strength, he acknowledged, the temptation is to compete everywhere. But strategy requires segmentation.
“Watch the sweet spot,” he said, calling it “a classic old-school management school segmentation.”
In his view, that sweet spot is software. “I think India’s power, the expertise is in the software side,” he explained. While four or five companies may dominate global frontier models, “there are far more opportunities in the next software.”
Rather than worrying about developing foundational models in India, he argued, the focus should be on building software and services on top of them. “It shouldn’t be a vanity thing… It is the right place to build the software capability on it and build the services capability.”
India’s Hidden Asset
Ramkumar Narayanan, EVP, Head of India and Philippines, AI Technology Enablement, FIS, broadened the lens to geopolitics. With export controls tightening, he cautioned that building strategic capabilities “can’t be stood up overnight.”
But he pointed to an underappreciated Indian advantage—what he described as the “context graph.” “If you think about agentic AI, the agents need a brain to operate on, which is the context graph underneath,” he said.
Over decades, Indian IT services firms and GCCs have accumulated deep enterprise process knowledge. “The process knowledge of most of the enterprises is actually locked up in a lot of these organisations,” he said. The challenge—and opportunity—is unlocking it.
India’s leverage may not be chips or sovereign models alone, but the structured understanding of how global enterprises actually function.
Lalitha Indrakanti, CEO of Jaguar Land Rover – Technology and Business Services India, underscored India’s structural advantages in the AI era. “Irrespective of the domain, what we're operating in India is being central to most of the organisations.”
On cost competitiveness, she noted, “As much as we say cost is no longer the reason, still having the cost advantage doesn't hurt, especially in today's very volatile situation in terms of the tariffs and all of that.”
Pointing to policy tailwinds, she said, “If you look at the whole trade deals that are getting signed, be it UK-India trade deal or India-EU trade deal… a lot of these things are very strongly giving a predictable roadmap for organisations.” She also acknowledged that the Budget 2026 announcements also make it conducive for GCCs by offering predictability and stability.
The “Four I’s” of AI
Jay Doshi, MD and CIO, BT Group, reframed the debate through what he called AI’s “four I’s”: “intelligence, infrastructure, influence and innovation.”
Rather than focusing narrowly on infrastructure dominance, he argued that success lies in balancing these forces. “I don’t probably believe in this whole debate that those who control the infrastructure will control the AI play,” he said. “Those who balance these four, market economics will play out.”
India’s demographic advantage—a younger workforce able to shift from “creator to orchestrator and producer”—could accelerate adoption. Doshi noted that unlocking processes and data debt represents a large share of AI’s value.
The harder question, however, is execution.
Hardest Shift for IT Services
When the discussion turned to Indian IT firms, Debashis Chatterjee, Board Member at US-based software engineering services company Ascendion, noted that COVID-19 forced companies to move from talking about digital to becoming digital. AI, he suggested, will be similarly transformational.
“This is a great opportunity for services firms to truly become outcome-based,” he said. While outcome-led delivery has long been discussed, “I don’t think it is kind of industrialised.”
He sees opportunity in tackling technical debt through AI and agentic tools. But the toughest challenge lies elsewhere: talent.
“Talent transformation at scale, in order to adapt to AI at scale, is going to be the biggest challenge,” he observed.
Others were more blunt. “AI is a great amplifier,” Doshi said.
Smaller AI development pods mean that “even one of the weakest links will amplify multi-fold,” he added. This is not “tinkering around the edges.” It demands rethinking the engagement model, the global delivery model, and even the pyramid structure on which Indian IT scaled for decades.
Chief AI Officer Role
The talent challenge has elevated an unexpected role: the CAIO.
Puneet Kaur Kohli, Chief Technology Information Officer, Generali Central Life Insurance, described AI as “a cultural shift” rather than just a technology initiative.
“It’s not the only responsibility of the technology department in any organisation,” she said. “It’s a discipline within.”
She argued that adoption must move beyond building a Chief AI Officer on the technology side. Instead, organisations should “start building an AI technology officer from the business side, who knows the game better.”
Your reaction
Discussion
What's your take on this story?
No comments yet — be the first to share your view.