New Delhi, July 8 -- India's global capability centres (GCCs) are entering a new phase of evolution as enterprises shift from using them as delivery hubs to giving them ownership of AI platforms, products and business outcomes. As organisations race to operationalise artificial intelligence, the focus is moving beyond scale and cost arbitrage towards specialised engineering talent, governance and enterprise-wide innovation.
In an interview with TechCircle, Sailaja Josyula, Senior Vice President and Global Head, GCC Service Line, Cognizant, discusses why execution-led GCCs risk being left behind, how AI is reshaping talent strategies, and why India's next competitive advantage will depend less on size and more on its ability to build enterprise AI at scale. Edited excerpts.
GCCs were once seen primarily as cost centres. What is driving their transformation into innovation hubs?
The shift is far more fundamental than a gradual evolution. Enterprises are redesigning their operating models around AI, data and digital platforms, and that has changed the role GCCs play. Instead of simply executing work defined elsewhere, they are increasingly shaping enterprise strategy and creating business value.
This transformation is happening from both ends. Global enterprises are pushing more strategic work into GCCs because AI demands speed, scale and specialised engineering capabilities. At the same time, India's talent ecosystem has matured significantly, giving GCCs the leadership depth needed to take on greater ownership.
The pace of AI adoption makes this transition even more urgent. AI exposure across jobs is increasing much faster than expected, which means centres focused only on execution risk becoming less relevant.
You've said AI-first talent is becoming the new competitive advantage - what does that actually look like in terms of hiring and capability building?
AI-first talent is not simply about hiring more AI specialists. It is about developing professionals who can take AI models from proof of concept to production, deploy them in regulated enterprise environments and remain accountable for business outcomes.
That requires engineers capable of building reusable AI frameworks rather than one-off solutions, product leaders who understand model performance and governance, and business leaders who can translate AI capabilities into measurable commercial value. At Cognizant, we have focused on transforming our own workforce first. Learning pathways are directly linked to project roles, ensuring AI capability development is tied to real business outcomes rather than certification alone.
Does India genuinely have the deepest AI talent bench globally, or are there still gaps in specialised skills??
India's advantage goes beyond scale. The country has built considerable expertise in applied AI engineering-taking models into production, integrating them with complex enterprise systems and operating within governance and regulatory requirements.
The next opportunity lies in moving further up the value chain. Areas such as foundation models, hardware-level AI, domain-specific engineering and highly regulated industries will define the next phase of India's leadership. The ecosystem-including universities, startups and GCCs-is already moving in that direction, making the shift from deployment excellence to deeper AI innovation.
How are GCCs redefining their role within global enterprises in an AI-first world??
The biggest shift is ownership. Today, GCCs are increasingly responsible for products, platforms and business outcomes rather than simply delivering technology projects. Whether it is fraud management in banking, clinical AI in healthcare or enterprise platforms, accountability now extends to customer outcomes, regulatory compliance and operational performance.
The Citizens Bank GCC in Hyderabad is one example, where the centre owns Citizens Pay and several private banking capabilities. That illustrates how GCCs are influencing product strategy and enterprise decisions rather than merely supporting headquarters. The most mature GCCs now operate with the same governance frameworks, KPIs and decision-making authority as global teams, making them strategic business centres rather than delivery organisations.
How are enterprises balancing speed of AI adoption with governance, risk and compliance within GCCs??
The most successful organisations no longer see governance as something that slows innovation. Governance becomes a constraint only when it is introduced after AI systems are deployed. When compliance, auditability and model governance are designed into the architecture from the outset, they actually accelerate enterprise adoption because organisations can scale AI with greater confidence.
The biggest risks emerge when companies build fragmented AI pilots across different business units without common controls. The leading GCCs are addressing this by centralising AI governance, model lifecycle management and compliance, creating platforms that make experimentation repeatable and scalable.
Which sectors are seeing the most transformation led by India-based GCCs, and why?
BFSI, healthcare, retail and life sciences sectors are being reshaped, but the depth of transformation depends on how far the GCC has moved from execution to ownership.
In BFSI, ownership is most pronounced. The work that banks and insurers need most urgently - fraud detection, AML, KYC, real-time risk - demands regulatory precision and judgment operating together at speed. India's financial services GCCs have built genuine depth in exactly this combination, and this is where I see ownership going well beyond activity. In healthcare, GCCs are engineering the platforms behind care delivery, claims modernisation, and revenue cycle outcomes, with responsible AI and clinical data governance at the core. In life sciences, the work sits in some of the most validated, regulated environments anywhere - drug discovery, pharmacovigilance, regulatory submissions - where precision and compliance are non-negotiable. In retail, GCCs are taking ownership of digital storefronts, AI-led merchandising, and supply chain intelligence in ways that are directly tied to revenue.
Is the current pace of GCC expansion in India sustainable, or do you see signs of saturation in talent or infrastructure?
The fundamentals remain extremely strong, but the conversation is changing. The next phase of growth will be defined less by the number of centres established and more by the quality of capabilities they build. Specialised AI talent remains scarce, while capacity constraints in mature hubs are encouraging organisations to expand into Tier-2 cities and rethink workforce models. India has significant structural advantages through its engineering ecosystem, digital infrastructure and talent base. However, maintaining leadership will require sustained investment in specialised skills and AI-centric operating models.
Looking ahead, will India remain the global command centre for GCCs, or are other geographies starting to compete meaningfully?
India remains exceptionally well positioned, but the basis of its leadership is evolving. The first phase of the GCC story was built on scale, efficiency and cost competitiveness. The next phase will depend on whether India can lead enterprise AI, own mission-critical platforms and influence strategic business decisions.
Other countries are strengthening their GCC ecosystems, but India's combination of engineering depth, domain expertise, experienced leadership and ecosystem maturity remains difficult to replicate.
The real challenge now is not preserving India's relevance but converting today's advantage into leadership in the higher-order AI capabilities that will define the next generation of global enterprises.
Published by HT Digital Content Services with permission from TechCircle.