The leadership shift: How India's GCCs are becoming launchpads for enterprise leaders

India’s Global Capability Centres (GCCs) are entering a defining phase. For many years, they were admired for engineering depth, execution discipline, and scale. Today, as AI becomes central to how enterprises operate, global organisations are entrusting Indian GCCs to play a more strategic role—shaping platforms, modernising offerings, strengthening governance, and building the required leadership capacity for AI-first organisations. This is more than a change in mandate. AI is changing and democratising how global enterprises are organised. The traditional distinction between strategy being defined at headquarters and execution taking place elsewhere is steadily giving way to a more integrated model, where decisions, innovation and leadership are distributed across geographies. Today, GCCs are becoming strategic engines for innovation, product ownership, and value creation.

India, now home to 2,100+ GCCs, has become the global epicentre of this transformation. The scale is important, but the more significant story is structural: GCCs are increasingly moving from delivery scale to enterprise ownership, and from talent availability to leadership density. The opportunity is no longer defined simply by the size of India’s talent pool. It is increasingly defined by the kind of leaders these centres develop: leaders who can connect technology with business, lead global initiatives and create value across markets.

Beyond delivery: From execution to enterprise ownership

Much has been written about the evolution of GCCs from cost-efficient delivery centres to strategic innovation hubs. That evolution is now entering a sharper phase and AI is accelerating this shift. For GCCs, the question is no longer whether teams can adopt AI tools. It is whether they can redesign workflows, talent models and governance so AI becomes a scaled operating capability rather than a collection of pilots.

As a result, success is being measured differently. Delivery metrics still matter, but they are no longer enough. Customer impact, product innovation, cycle-time reduction, risk mitigation and business value are becoming equally important. As ownership expands, GCCs need leaders who can connect engineering depth with commercial acumen, and automation ambition with responsible governance.

AI-native GCCs and the rise of new organisation structures

AI is also changing how organisations are designed. Current structures are built around functions, competencies, and layers. AI-native organisations are beginning to re-structure around value streams, platforms, and human-AI teams. In this shift, the GCCs become less of a location-based delivery unit, but more of a capability system that brings together product owners, engineers, data scientists, domain experts, risk teams and AI specialists around enterprise outcomes.

This has practical implications. A product team may now have AI agents that assist in delivery, coding, testing, documentation, incident analysis or customer support. Programme managers and scrum masters are evolving from task owners into value-orchestration leaders who can interpret signals, remove constraints and ensure responsible adoption. Architects and domain leaders become even more critical because they define the guardrails, Business & data context, interoperability and business logic that allow AI to scale safely.

For GCCs, the structural shift is especially powerful. A mature GCC can become the place where the enterprise learns how to work with AI at scale: where workflows are redesigned, reusable patterns are built, responsible AI controls are tested, and learnings are shared across global business units. In other words, GCCs can become the enterprise’s AI operating laboratory as well as its leadership factory.

From AI pilots to enterprise value: The new GCC CoE (Centre of Excellence) mandate

Recent industry data reinforces this shift. EY’s GCC Pulse Survey 2025 reports that 83% of India GCCs are investing in GenAI, and two-thirds are creating dedicated innovation teams and incubation programmes to generate, test and globalise ideas from India. The direction is clear: AI is moving from experimentation to operating-model redesign.

This creates a new mandate for GCC-led Centers of Excellence. A CoE can no longer be only a specialist group that publishes standards or runs proofs of concept. It must operate as a value engine with end-to-end responsibilities: identify the right business problems, build reusable technology and data assets, embed governance and adoption discipline, and measure impact in business terms.

The best CoEs of the future will be multidisciplinary. They will combine AI engineering, platform architecture, security, legal and compliance, domain knowledge, change management, workforce learning and value management. Their purpose is not to centralize all AI work, but to create a repeatable system through which distributed teams can adopt AI faster, safer and with clearer accountability.

This is where GCCs have a natural advantage. They sit close to the enterprise’s technology backbone and increasingly close to business priorities. They can see patterns across products, operations and customers, and convert those patterns into reusable accelerators. Done well, a GCC-led AI CoE becomes the bridge between local experimentation and global scale.

Building enterprise leaders requires deliberate investment

Leadership, however, does not emerge automatically as organisations grow. As GCCs continue to mature, developing leaders become as intentional as developing technology capabilities. This means creating opportunities for professionals to gain international exposure, participate in customer-facing roles and take ownership of business-critical initiatives early in their careers, while giving them the trust to make decisions with enterprise-wide impact.

At Amdocs India, we have found that leadership grows faster when people are given opportunities to manage global roles like select product lines, collaborate across markets and engage directly with customers. These experiences help develop leaders who can think beyond functional excellence and drive enterprise outcomes.

The same principle applies to AI adoption. Leaders must be enabled not only to use AI, but to sponsor AI responsibly, judge the right use cases, understand data and security implications, and lead teams through the discomfort of change. AI fluency should therefore become part of leadership development, not a separate technical curriculum. Organisations must also foster a culture of curiosity, accountability and continuous learning. Technical expertise will remain essential, but the leaders who thrive will also demonstrate sound judgement, collaboration and the ability to lead through change. These human capabilities are becoming even more valuable as AI takes on more deterministic and repetitive work.

As GCCs continue to take on broader responsibilities, they have an opportunity to become launchpads for enterprise leaders, professionals who can connect the cords of technology and business, navigate complexity and help shape the future of global organisations. That may well become India’s most significant contribution to the global enterprise in the decade ahead—not just as a source of talent, but as a source of enterprise leadership for an AI-native world.

(The author is division president, Amdocs India & Global Operations. Views are personal.)