Something profound is happening in the geography of technological power, and most of us are only beginning to notice. While Silicon Valley debates AI safety and European regulators draft frameworks, a quieter revolution is unfolding across Bangalore, Hyderabad, and Pune. India's Global Capability Centers—once dismissed as back-office cost arbitrage plays—are becoming the factories where enterprise AI is actually built, governed, and scaled.
The bigger question isn't whether this shift is happening. It's what it means when the world's largest corporations increasingly depend on Indian centers not just to execute their AI strategies, but to architect them.
The Numbers Behind the Transformation
The scale of India's GCC ecosystem has reached a tipping point that demands attention. According to Zinnov's 2025 analysis, 1,760+ Global Capability Centers now operate in India, employing 1.9 million professionals. But the raw numbers obscure the more interesting story: the nature of work these centers perform has fundamentally changed.
The ANSR Report 2025 reveals that 126,000+ professionals now work specifically in AI roles within India's GCCs—a concentration of enterprise AI talent that rivals or exceeds most Western tech hubs. This isn't incremental growth; it's a structural reorganization of where AI capability resides.
Consider the velocity: approximately 50 new GCCs opened in India in H1 2025 alone. More telling is the projection that mega GCCs will grow from 88 in 2025 to 230+ by 2030—and these mega centers are 1.5x more invested in DeepTech domains like AI, cloud infrastructure, and cybersecurity than average centers.
From Cost Centers to Capability Creators
The traditional narrative of offshoring was simple: labor arbitrage. Send routine work to lower-cost locations, capture the savings, maintain strategic control at headquarters. That model is becoming obsolete.
BCG's 2025 research on India's GCC evolution highlights a fundamental shift in mandate. These centers are no longer executing strategies designed elsewhere—they're increasingly responsible for platform R&D, AI governance frameworks, and innovation roadmaps that shape their parent companies' competitive positioning.
Zinnov reports that nearly 9 in 10 large GCCs now operate at "Portfolio" or "Transformation" maturity levels—meaning they own entire product lines or drive enterprise-wide change initiatives, rather than simply supporting them. When Infosys unveils AI-first GCC models, it's signaling that the industry recognizes this isn't a temporary trend but a permanent restructuring.
The implications are worth sitting with. When AI governance—the rules determining how models are trained, deployed, and monitored—is designed in Hyderabad for deployment in Houston, something has shifted in the locus of technological decision-making.
Three Perspectives on What This Means
The Optimist's View: This represents the democratization of innovation. India's engineering talent, combined with deep domain expertise accumulated over two decades of enterprise IT work, creates a virtuous cycle. GCCs attract better talent, which enables more sophisticated work, which attracts more investment. The result is a genuine multipolar technology world where innovation emerges from multiple centers rather than being concentrated in a few Western hubs.
The Skeptic's View: Capability without ownership is still dependency. Indian GCCs may build the AI, but the strategic direction, IP ownership, and ultimate value capture remain with headquarters. This is a more sophisticated form of the same arbitrage—intellectual labor arbitrage rather than simple cost arbitrage. The fundamental power asymmetry persists.
The Realist's View: Both dynamics are true simultaneously. GCCs are gaining genuine capability and influence, but within structures designed to channel value to parent companies. The interesting question is whether this equilibrium is stable, or whether capability accumulation eventually translates into different organizational forms.
Second-Order Effects Worth Watching
Global talent market restructuring: If enterprise AI expertise concentrates in India, what happens to AI career paths in the US and Europe? We may see a bifurcation: research and frontier model development in one geography, enterprise implementation and governance in another. This has profound implications for technical education and immigration policy.
The rise of "AI governance as a service": As GCCs develop sophisticated frameworks for responsible AI deployment across regulated industries, this expertise becomes exportable. Indian centers may become the de facto standard-setters for enterprise AI governance—not through regulation, but through accumulated practice.
Startup ecosystem effects: Oliver Wyman's analysis suggests GCCs are increasingly spinning out ventures and partnering with local startups. When 126,000 AI professionals work in close proximity, the density effects on entrepreneurship could be significant. India's next generation of AI companies may emerge not from traditional startup ecosystems, but from GCC alumni networks.
What Comes Next: Three Scenarios
Scenario 1: Acceleration. The trend intensifies. By 2030, Indian GCCs don't just implement AI—they lead global AI strategy for major enterprises. Headquarters become primarily commercial and regulatory interfaces while technical leadership migrates to capability centers.
Scenario 2: Rebalancing. Western companies, recognizing strategic dependency, deliberately diversify their capability center geography. Vietnam, Poland, and Mexico see accelerated GCC growth. India remains dominant but not monopolistic.
Scenario 3: Transformation. The GCC model itself evolves. Rather than captive centers serving single parent companies, we see the emergence of shared capability platforms—consortiums of companies pooling AI development resources in India. The "center" becomes an ecosystem.
A Framework for Thinking About This
When evaluating the GCC evolution, ask three questions:
- Where does the learning accumulate? In any technology development process, knowledge compounds. If the learning happens in India, the long-term capability advantage accrues there—regardless of where IP is legally owned.
- What decisions require proximity? Some strategic choices require being close to customers, regulators, or markets. Others don't. As AI governance becomes more codified, the decisions that require headquarters proximity may shrink.
- Who trains the next generation? Perhaps most importantly: where do tomorrow's AI leaders develop their expertise? The answer to that question, more than any current statistic, will determine the long-term geography of AI power.
The GCC evolution is not just an India story or an offshoring story. It's a leading indicator of how AI reorganizes not just workflows, but the entire geography of technological capability. The shift from "capability centers" to "capability creators" may be the most consequential—and least discussed—transformation in global technology.
The question isn't whether India's GCCs will matter. It's whether we're prepared for a world where they matter this much.