How GCCs are becoming the core of AI led enterprise reinvention

For years, India's global capability centres (GCCs) have been celebrated for their ability to scale talent, contain costs, and deliver technology reliably for global enterprises. That narrative is now changing and changing fast. In the age of artificial intelligence, the question is no longer whether GCCs can execute well. It is whether they can lead.

The shift goes beyond adding AI tools to existing workflows. What is emerging is a more fundamental redefinition of purpose: GCCs are being called upon to shape enterprise outcomes, redesign how work is structured, orchestrate ecosystems of partners and platforms, and drive AI adoption at a scale. To do this, they need to be embedded in business strategy, not insulated from it.

This was the central theme of a recent Times Techies roundtable, held in partnership with Accenture, where leaders from some of the world's most consequential enterprises came together to discuss the next chapter of the GCC story. What emerged was both a clear assessment of where most centres stand today and an ambitious blueprint for where the best of them are headed.

From execution centre to AI catalyst
Not all GCCs are at the same stage of this journey. Paul Jeruchimowitz, Senior Managing Director and Global GCC Practice Lead at Accenture, highlighted a striking insight: “According to our latest research with 250 GCC leaders across India, 29% are already operating as true catalysts for enterprise-wide transformation and innovation. Scaling AI has laid the foundation, but designing for outcomes is what creates real impact. The leaders who will define the next stage are already solving problems their enterprise hasn't asked them to solve yet.”

These leading centres share two distinguishing traits: they actively influence how work gets done across the broader business, and they invest heavily in both business acumen and AI capability, often developing a level of AI fluency that outpaces their own headquarters, allowing new ways of working pioneered in India to be ported back to the global enterprise.

Lalit Ahuja, Founder & CEO of ANSR, underscored that AI adoption is fundamentally about context. For GCCs to stay relevant, they must become the institutional repository of enterprise knowledge - the data relationships, process understanding, and organisational memory that makes AI outputs trustworthy and applicable. "AI will be the biggest change management challenge enterprises have faced in a long time, because it will fundamentally reshape how work is distributed, who does it, and what skills matter," he said. "GCCs are uniquely positioned to lead this transition because they can hire at scale, build infrastructure, and drive experimentation. As AI adoption accelerates, success will increasingly depend not just on IQ or EQ, but on “AIQ” -- the ability to work effectively with AI and adapt to new ways of working”, he added.

Getting the foundations rightThe ambition to scale AI runs into a common and uncomfortable truth: most organisations are simply not ready for it. The barriers are rarely technological - they are structural, cultural, and organisational.
Leaders at the roundtable pointed to several foundational challenges that must be addressed before AI can deliver at scale:

• Data quality and trust: AI models, particularly large language models, perform best when given rich, well-organised context. But many enterprises still manage data as collections of documents rather than as structured, governed assets. Fragmented data pipelines and siloed systems produce inconsistent inputs, which in turn produce unreliable outputs.
• Governance redesign: Traditional enterprise governance is built around control and prevention. AI demands different systems designed to catch errors dynamically, feedback loops that improve results over time, and a culture of psychological safety that allows teams to surface failures early without fear.
• Organisational readiness: Technology is rarely the constraint. It is the processes, roles, and mindsets around it that determine whether AI can scale.

Hari Krishna Verma Nadimpalli, Managing Director of Inspire Brands' India Innovation Centre which oversees restaurant and quick-service food brands including an ice cream chain, a coffee-and-doughnut chain, and a casual dining wings restaurant chain, has seen this firsthand. His team uses data and AI to understand customers more precisely, predict demand, and estimate customer lifetime value. But the real work, he noted, lies in the infrastructure surrounding the model. "It is all the processes that go around that make it scalable," he said. As Nadimpalli put it, “the old assembly-line model of work, where ideas move from product to engineering to quality assurance to deployment, will give way to a craft-based model. Roles will blur. People will need adjacent skills. The question will not be whether someone can write perfect syntax, but whether they can think in systems, explain AI decisions and use AI responsibly."

"In complex and regulated environments, Global Capability Centers such as our Deutsche Börse Group Hub in Hyderabad succeed when AI is anchored in strong data ownership, accountable governance, and enterprise trust, enabling innovation that is reliable, auditable, and scalable,” says Dr. Ludwig Heinzelmann, Director and Head of Deutsche Börse India.

To embed this approach, Deutsche Börse established a transversal Chief Digital Transformation role to drive AI, data, and cloud transformation across the group. Its Hyderabad centre, launched in August 2024, is positioned as a scaled hub for enterprise-wide innovation and execution.

The road ahead
One of the more consequential shifts to emerge from the roundtable was the expanding role of GCCs as ecosystem orchestrators. When the pace of change is this rapid, no organisation can build everything internally, some solutions must be acquired, others assembled through networks of startups, platform providers, academic institutions, and specialist service firms.

Jeruchimowitz pointed to a structural advantage GCCs hold here: by bringing together technology, business functions, and talent under one roof, and sitting at the intersection of global enterprise demand and India's rich innovation ecosystem, they are uniquely positioned to orchestrate rather than simply consume. Ahuja echoed this, noting that the best GCCs are increasingly opening themselves up to the ecosystem around them, functioning less like captive units and more like platforms, with the role of a GCC head evolving from operations manager to ecosystem architect, someone who knows not just how to build, but when to partner, when to acquire, and how to integrate external innovation rapidly into the enterprise.

What emerged from the roundtable was a clear message that the GCC of the next decade will be fundamentally different from the model that came before it. Industry leaders indicated that future-ready centres will be those that move beyond execution and delivery to play a more strategic role, evolving into innovation engines that are AI-fluent, ecosystem-connected, and deeply embedded in solving core business challenges.

The window for that transition is open, but it will not stay open indefinitely. As Jeruchimowitz put it, the leaders who will define the next stage are already solving problems their enterprise hasn't asked them to solve yet. That is the measure of a true catalyst: not waiting for the agenda, but writing it.

Disclaimer: This article has been produced on behalf of Accenture by Times Internet’s Spotlight team.

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