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How AI-First Platforms Transform GCCs from Ops Hubs into Innovation Powerhouses

July 21, 2026

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Global Capability Centers (GCCs) are at a pivotal crossroads. Traditionally viewed as cost-efficient operational hubs, they are now transforming into engines of strategic innovation in the AI era.

As enterprises demand greater agility and faster delivery, GCCs are expanding beyond back-office functions into high-value roles like R&D, digital transformation, analytics, and product engineering. This shift is already underway. The fast-paced AI evolution is putting additional pressure on GCCs to drive innovation, accelerate decision-making, and deliver measurable business outcomes, within shorter timeframes and budgets.

To fully realize the value of their GCC investments, leaders must address two critical questions:

The answer lies in adopting an AI-first operating model built on unified platforms that enable GCCs to move beyond incremental efficiency gains and become intelligence-driven engines of transformation.

Overcoming Barriers: From Cost Centers to AI-Native Innovation Engines

Historically, GCCs followed a slow maturity curve—from low-cost operations centers to process excellence hubs, then to innovation centers, and ultimately to strategic global offices. Increasingly, however, many greenfield GCCs are bypassing the early stages altogether, launching directly as innovation hubs focused on advanced engineering and digital capabilities.

The catalyst enabling this leap is AI. However, tapping AI capabilities is far from easy unless organizations adopt a strategic and unified approach addressing challenges spanning people, process, data, technology, and others. This is where AI-first platforms, specifically curated to address these challenges and accelerate AI-led transformation, truly shine.

With AI-first platforms, GCCs can unify fragmented operations, intelligently automate repetitive tasks, augment decision-making with real-time intelligence, and scale capabilities without linear headcount growth. In doing so, GCCs move from support functions to core drivers of enterprise innovation. This shift frees teams to redirect their efforts toward higher-value work, such as design, customer experience, and other strategic initiatives, creating a more agile, intelligence-led operating model.

At the core of this transformation is Infosys Topaz AI Next (earlier called EdgeVerve AI Next), a unified AI platform that integrates predictive, generative, and agentic AI with data transformation and intelligent automation to reimagine enterprise operating model with an AI-first agenda.

Powering AI-Native GCCs and Unifying AI-Driven Operations

Despite their potential, many traditional GCCs struggle with fragmented systems, manual workflows, and siloed operations that dilute their strategic impact. To truly act as an enterprise engine, GCC operations must be seamless and business outcomes-oriented.

Operations & Service Management (OSM)—a curated solution for GCCs powered by Topaz AI Next platform—addresses business operations’ inefficiencies through a unified, AI-driven architecture by:

The result is faster decision-making, smarter operations, and scalable value creation.

Download the latest Forrester best-practices report to learn how Infosys Topaz AI Next (earlier called EdgeVerve AI Next) can help unleash the full potential of your GCC.

Data Intelligence as the New Currency

As GCCs take on more strategic mandates, high-quality data becomes their most critical asset. Fabric, an intelligent data integration and transformation capability within the Topaz AI Next platform, supports this shift by allowing GCCs to integrate, cleanse, and contextualize data from disparate enterprise systems at scale, making it AI-ready.

This continuous feed of real-time inputs into AI models creates a powerful closed-loop system:

Data → AI Models → Insights → Actions → Improved Outcomes -> Feedback loop

Over time, this continuous cycle drives higher accuracy and stronger business impact.

The Path Forward: AI-Native, Enterprise-Embedded GCCs

The divide between GCC leaders and laggards is widening in the AI era. GCCs relying on legacy models, fragmented systems, and “experiment-heavy” approach to AI risk stagnation, while those boldly rewiring their service models with a more holistic and unified platform-based approach are leaping ahead, redefining enterprise-wide transformation and gaining competitive edge.

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