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Every Enterprise is trying to transform with AI. But most are looking in the wrong direction.
They’re waiting for headquarters to set the roadmap, for global teams to drive strategy, for top-down initiatives to unlock enterprise-scale change. But the real transformation won’t come from the top. It will come from the parts of the organization that know how to rebuild from the inside.
It will come from the Global Capability Centers (GCCs).
If AI is forcing enterprises to rethink how they work, that transformation won’t start at the top. It will start where change is both possible and practical. That’s why the real momentum is building inside GCCs.
These centers already bring together product, engineering, data, and operations under one roof. They operate with speed, have full visibility into processes, and are used to owning outcomes. And this isn’t new territory. GCCs were instrumental in driving digital transformation and automation at scale. That experience now puts them in a strong position to lead the shift toward AI-native models.
In an AI-native operating model:
In pockets across the ecosystem, these changes are already underway. AI-first hiring, AI-led development, and agentic process design are being prototyped and deployed in GCC floors across India. The future is already being built. The challenge is to scale it.
So how do you actually become an AI-first GCC?
Start by shifting the frame. This is more about ownership, not just tools.
The most successful transformations begin by picking a process, recruitment, development, finance, and breaking it down to its smallest tasks. Then reimagining each step with an AI agent in mind. Not as a workflow automation exercise, but as a fundamental redesign.
The second shift is in structure. Collapse unnecessary layers. Co-locate interdisciplinary teams. Build what one leader described as “zero distance” between prompt engineers, data scientists, product owners, and business users. Structure follows strategy, and AI-first strategy needs agile, empowered teams.
Third, build for outcomes, not activities. The real differentiator of a GCC is not how many projects it executes, but how well it understands the customer. Whether internal or external, every engineer, analyst, or program owner must anchor their work in measurable business impact.
And finally, build the infrastructure; data, compliance, governance, that enables scale. GCCs that can create robust data architectures and agent orchestration frameworks will become the backbone of enterprise-wide transformation.
The playbook is there. What’s needed now is conviction.
GCCs have led digital and automation waves before. This is their chance to lead again by shaping the AI wave. Because the truth is, the AI revolution needs builders.
If this resonates with where your organization is headed, or where it needs to be, you’ll find deeper frameworks, case stories, and starting points in the full keynote.
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