For years, India’s global capability centres were seen through a narrow lens. They were the offshore arms of multinational companies, built to deliver efficiency, scale and cost advantage. The work was important, but the perception was clear: these centres were execution hubs, not strategic command centres.
That perception is now changing fast.
Across Bengaluru, Hyderabad, Pune, Chennai, Gurugram and Mumbai, the new GCC is being built less like a back office and more like an enterprise AI lab. Global companies are using their India centres to design data platforms, build automation layers, deploy AI assistants, develop proprietary models, modernise cloud infrastructure, run cybersecurity operations, create customer intelligence engines and increasingly own end-to-end technology mandates.
The latest Nasscom-Zinnov report captures the scale of this transition. India now hosts 2,117 GCCs across 3,728 units, employing 2.36 million professionals and generating $98.4 billion in revenue in FY26. The number is significant not only because the sector is nearing the $100-billion mark, but because the nature of the work has changed. The report describes the shift as one from a “delivery engine” to an “enterprise nerve centre.”
That phrase is important. It suggests that GCCs are no longer peripheral extensions of global enterprises. They are becoming part of the core operating system.
The old India GCC story was built around labour arbitrage. The new one is built around capability arbitrage. Multinational companies are no longer coming to India only because the talent is cheaper. They are coming because India has deep pools of engineers, data scientists, product managers, cybersecurity experts, cloud architects and increasingly, AI specialists who can work on complex global problems at scale.
Artificial intelligence has accelerated that shift. In the pre-AI era, a GCC was often measured by headcount, efficiency, process maturity and delivery volume. In the AI era, those metrics are being replaced by model deployment, automation depth, intellectual property creation, product ownership, time-to-market acceleration and measurable business impact.
This does not mean the sector is immune to disruption. In fact, AI is also forcing a hard reset. A recent Reuters report quoted Lalit Ahuja, founder and CEO of ANSR, as saying, “There is a sense of cautiousness.” He added that companies are hiring fewer people as a matter of abundant caution, with some firms scaling back earlier plans for very large centres. The same report noted that AI and geopolitical uncertainty are making companies more measured in how they build and expand GCCs.
That caution, however, does not signal a slowdown in relevance. It signals a change in the kind of relevance global companies now want.
The next GCC will not win by being bigger. It will win by being smarter.
This is already visible in how mandates are being structured. GCCs are increasingly being asked to build AI-enabled enterprise systems rather than merely support them. The work spans enterprise data architecture, generative AI pilots, agentic workflows, cloud migration, business intelligence, fraud detection, marketing automation, product engineering, supply chain intelligence and customer experience transformation.
In retail, banking, healthcare, manufacturing and technology, India centres are being pulled closer to global decision-making. Reuters recently reported that Catalyst Brands, the parent of brands such as Aeropostale, plans to expand its Bengaluru GCC to around 1,000 employees by the end of the year. Nihar Nidhi, India managing director of Catalyst Brands, said the scale and quality of AI use cases emerging from Bengaluru are raising expectations that “Bangalore will lead the agenda” in the future.
That statement reflects a larger truth. India’s GCCs are no longer simply receiving technology roadmaps from headquarters. In several cases, they are helping write them.
The rise of enterprise AI has made this shift more urgent. Most large companies now face the same problem: they have access to powerful models, but they do not yet have the architecture, governance, data quality, security controls or internal workflows needed to use AI meaningfully. Buying AI tools is easy. Rebuilding the enterprise around AI is hard.
That is where GCCs are beginning to matter.
A serious AI stack for a global enterprise is not just a chatbot. It requires clean and connected data, cloud infrastructure, cybersecurity, application modernisation, workflow integration, model governance, compliance, domain context and adoption across business teams. These are precisely the areas where mature GCCs have spent years building capability.
The difference now is that these capabilities are being fused into AI-led operating models.
Microsoft Chairman and CEO Satya Nadella has described AI as a major platform shift, comparable to earlier shifts such as the internet, mobile and cloud. For global enterprises, that platform shift cannot be managed only from headquarters. It needs distributed centres of excellence that can translate AI ambition into working systems. India’s GCCs are increasingly becoming those centres.
Google CEO Sundar Pichai has also framed enterprise AI as a new cloud opportunity, with AI agents, models and infrastructure becoming central to how companies work. Nvidia CEO Jensen Huang has spoken of “AI factories” as a new production model for intelligence, arguing that companies will need full-stack AI infrastructure to produce tokens, insights and automation at industrial scale. These global comments may not be specifically about Indian GCCs, but they explain why the GCC model is being reimagined. If every large company needs its own AI factory, India is positioning itself as one of the most important places where those factories will be designed, staffed and run.
The change is especially visible in the movement from support functions to product and platform ownership. Earlier, a GCC might have maintained a company’s CRM, ERP or analytics dashboard. Today, it may be building the AI layer on top of those systems, creating predictive models for customer churn, designing recommendation engines, automating service workflows or developing internal copilots for employees.
In marketing and customer experience, this has direct implications. Global brands are using India centres to manage martech platforms, customer data platforms, campaign analytics, personalization engines, loyalty programmes and AI-led segmentation. As generative AI enters content, commerce, customer service and media planning, GCCs are becoming central to how brands industrialise AI in marketing.
This could create a new kind of competition for agencies, IT services firms and consulting companies. A brand that once outsourced campaign analytics or customer journey orchestration may now build those capabilities inside its GCC. A company that once depended on an external partner for AI experimentation may now use its India centre to create reusable AI assets. A marketing team that once waited for external dashboards may now get real-time intelligence from an internal global hub.
That does not mean agencies and IT firms disappear. But their role changes. They may need to move from execution partners to specialist collaborators, bringing strategy, creativity, domain depth or transformation support that complements the GCC rather than replaces it.
The sharper challenge is for the GCCs themselves. The hype around AI can easily outrun actual capability. Many centres still carry legacy workloads. A Business Standard report recently cited Zinnov’s view that a large share of GCC work remains vulnerable to AI-led disruption because it sits in commoditised processes. Pari Natarajan, CEO and co-founder of Zinnov, was quoted as saying, “The portfolio itself, the very foundation of a GCC, is now the most exposed layer.”
That warning matters. The same AI wave that is elevating GCCs can also expose them. If a centre remains focused on rule-based, repetitive, low-complexity work, it risks automation. If it moves into innovation, product ownership, AI governance and business transformation, it becomes more strategic.
The winners will be the GCCs that move up the value chain before they are forced to.
This transition will require new leadership models. The GCC head of the past was often a delivery leader. The GCC head of the future will need to act more like a business builder, technologist, transformation officer and talent strategist combined. They will need to understand global business priorities, not just India operations. They will need to manage AI risk, build cross-functional teams, retain senior talent and demonstrate business outcomes.
The talent model is also changing. In the old model, scale was an advantage. In the new model, the mix of talent matters more than the total count. Companies need fewer people doing manual process work and more people who can build AI systems, design prompts, govern data, train models, manage cloud costs, secure digital infrastructure and translate business problems into technology solutions.
That shift may make hiring more selective. It may also make GCC careers more attractive to high-end talent. For an engineer, product manager or data scientist, a mature GCC now offers exposure to global platforms, complex use cases and enterprise-scale AI deployment. In many cases, the work may be more global and more technically ambitious than what is available in traditional services roles.
This is why India’s GCC story has become more consequential than a simple employment story. It is now tied to the future of enterprise technology itself.
The global enterprise is entering a phase where every function wants AI, but few functions can implement it alone. Finance wants predictive risk systems. HR wants talent intelligence. Marketing wants personalization at scale. Supply chain wants demand forecasting. Legal wants contract intelligence. Customer service wants AI agents. Cybersecurity wants autonomous threat detection. Leadership wants real-time decision dashboards.
All of this requires a technology spine. GCCs are increasingly becoming that spine.
The question now is whether India can sustain this advantage. Other countries are also competing for global capability work. Eastern Europe, Southeast Asia, Latin America and parts of the Middle East are building their own delivery and innovation ecosystems. India’s edge lies in scale, depth, maturity and the density of its technology talent. But that edge will need constant upgrading.
For policymakers, the opportunity is clear. GCCs can bring high-value work, global exposure, advanced skilling, technology investment and stronger integration with multinational innovation networks. For companies, the opportunity is to turn India centres into enterprise transformation engines. For professionals, the opportunity is to move from process execution to AI-led problem solving.
But the transition will not be automatic.
A GCC cannot become an AI lab by changing its branding. It needs investment in data infrastructure, responsible AI frameworks, leadership capability, cloud architecture, domain expertise and business integration. It needs permission from headquarters to own outcomes, not just tasks. It needs to be measured on innovation, speed and value creation, not just cost savings.
That is the real shift underway.
India’s GCCs are not abandoning their delivery roots. Delivery discipline is still one of their strengths. But the centres that matter most in the next decade will combine that discipline with AI-native thinking. They will be able to take a business problem, connect the data, build the model, govern the risk, deploy the system and measure the impact.
The back office has not disappeared. It has evolved.
What once sat at the edge of the multinational enterprise is moving closer to the centre. India’s GCCs are no longer just supporting the global enterprise. Increasingly, they are helping build the intelligence layer on which the global enterprise will run.
Disclaimer: All data points and statistics are attributed to published research studies and verified market research. All quotes are either sourced directly or attributed to public statements.