Why AI-First Is Becoming the Defining Standard for Elite GCCs -By Piyush Kedia, Co-Founder and CEO, InCommon

Global Capability Centers (GCCs) are undergoing a major shift in their identity and operating purpose. Originally built as cost-efficiency and support extensions for global enterprises, GCCs are now transforming into strategic engines of innovation, speed, and outcome ownership. The evolution is no longer defined by offshoring or labor arbitrage, but by how effectively these centers can think, decide, and deliver with agility. At the core of this next phase lies an essential principle: being AI-first.

From Support Arms to Strategy Drivers

In the late 1990s, GCCs largely served as back-office units focused on operational execution and cost control. Global firms had only around 300 GCCs at the time, with fewer than 100 in India. By 2015, their role expanded to include digital transformation and research-driven mandates, with India hosting almost 800 of the world’s 1,200 GCCs.

Today, there are about 3,200 GCCs globally, and India accounts for nearly 1,700 of them. Yet, the newest phase of their evolution is just emerging — one in which GCCs take responsibility for outcomes rather than tasks. This is where the AI-first model becomes fundamental.

What It Really Means to Be AI-First

Being AI-first is not about simply adding automation layers or integrating AI copilots into existing workflows. The shift is structural. It requires embedding AI into the very architecture of how work is done.

In AI-first GCCs:

Feedback loops are shorter.

Decision-making is closer to the execution layer.

Performance is measured using real-time signals rather than retrospective reports.

These organizations are built to learn fast, decide fast, and ship fast.

Lessons From Microsoft’s Early Reorientation

In the early 2000s, Microsoft’s India engineering center could have remained a cost-efficient offshore hub. Instead, local teams were entrusted with genuine product ownership — developing critical components for platforms like Windows Defender, SQL Server, and Azure. When the company pivoted toward cloud and AI, the capability was already embedded.

This illustrates a broader pattern: GCCs that reorganize early around AI-first structures will gain compounding benefits in the long term.

The Shift Happening Now

Across India’s GCC ecosystem, decision-making is becoming sharper and more value-driven. Instead of broad experimentation pipelines, leaders increasingly prioritize initiatives with clear quarterly return metrics. Teams are gaining autonomy to build directly without long waits for licensing or infrastructure approvals. Hybrid Large Language Model (LLM) setups — combining cloud-based speed with on-premise control — are quickly becoming standard.

Pricing power is also changing. For decades, performance was measured through headcount and hours. Today, the metric is singular: what ships.

Traditional vs. AI-First: What Changes

Traditional GCC Model AI-First GCC Model

Centralized mandates Autonomous product pods

Siloed teams Integrated data, code, model workflows

Endless pilots with limited scale Rapid experimentation and deployment

KPIs on cost and capacity KPIs on velocity, quality, shipped outcomes

New roles are emerging — Prompt Engineers, LLM Product Managers, DataOps, AI QA, Model Risk/Ops — all aligned to ensure rapid and safe shipping outcomes.

A Simple Roadmap to Become AI-First

Make speed and value visible

Measure frequency of releases, time-to-fix, experiment velocity, and agent ROI.

Empower pods with ownership

Decisions should be made where work happens, not in distant corporate committees.

Invest in shared tools and guardrails

Reuseable prompts, frameworks, and evaluators enable scale and consistency.

Hire for shipped outcomes

Impact, not jargon, is what compounds advantage.

Integrate governance early

Data discipline and model risk management ensure speed is sustainable.

Why India Is Positioned to Lead

India’s talent density, problem-solving ecosystem, and maturing leadership culture give it a natural edge in building AI-first capability centers. Many global companies have already shifted core product mandates to their Indian GCCs. With the right structures, India is poised to anchor the next era of global outcome-driven innovation.

Delivering on the AI-First Promise

There are two common pitfalls: declaring “AI-first” without changing decision rights, or moving too fast without safeguards. Both are solved through:

Empowering teams closest to the work

Ensuring transparency of metrics

Designing systems that can be rolled back without disruption

What “Elite” GCCs Will Look Like in 2030

By the end of the decade, advanced GCCs will not just use AI — they will be structured around it. Autonomous yet accountable teams will treat models as practical tools, not black boxes. Organizational culture will be defined by how quickly teams iterate and learn.

GCCs have already evolved from support units to product engines. The next leap is where they become outcome organizations. In this journey, AI is not the end goal — it is the most powerful mechanism to reach it.