By: Ethan Lee

As enterprises work to quickly adapt in this rapidly evolving age of AI, experts suggest that AI-powered Global Capability Centers (AI-GCCs) are becoming increasingly important for businesses of various sizes, whether they have a few hundred or thousands of employees. While AI-GCCs are often seen as essential for helping businesses optimize operations, increase productivity, and reduce costs, the impact they have may vary depending on each company’s unique needs and circumstances. Insights shared by experts like Anil Chintapalli, Managing Partner at Human Capital Development and Senior Advisor to McKinsey & Company, illustrate how AI-GCCs can be a valuable asset to businesses seeking to transform their operations.

Anil, a distinguished technology investor and operator with over 30 years of experience, has been instrumental in the operationalization of over 40 GCCs globally, with a focus on improving efficiency and reducing costs through AI-driven solutions. His work has helped enterprises leverage AI to optimize various business processes. He is widely recognized for his role in the business transformation of WNS Holdings, which resulted in its sale to Capgemini for $3.3 billion.

Global Capability Centers (GCCs), sometimes called captives, global in-house centers, shared service or tech hubs, or Centers of Excellence, are fully owned parts of a company that focus on high-value work like engineering, data and AI, design, finance, risk, and customer experience. Unlike outsourcing, a GCC is operated by the company itself, which maintains its own culture, intellectual property (IP), plans, and security, but is located where skills and costs are most favorable.

“Think of AI-GCC as an AI-powered solutions factory that can scale your enterprise capability,” explains Anil. Over the past two decades, he has helped establish and operationalize more than 40 GCCs globally, applying an industrialized operating blueprint to expedite their setup while keeping costs manageable. “AI-GCC should be able to ship outcomes (such as product features, models, analytics, know-your-customer decisions, and anti-money laundering decisions), not just deliver cost savings. It can serve the entire gamut of enterprise needs at an accelerated speed to market, while optimizing costs: procurement, finance and accounting, human resources, information technology, sales and marketing operations, and more.”

Anil, who also serves on the Forbes Business Council and the Fast Company Executive Board, outlined the anatomy of AI-GCC, which includes four key components:

• Scope: Focus on optimizing software engineering, Artificial Intelligence (AI), Machine learning (ML), and cybersecurity operations, among others.

• Operating model: Product-centric technology and operations operated by agentic AI workforce squads mapped to business outcomes with shared enablement.

• Footprint: Flagship hubs in regions like India, plus satellite hubs to help support business continuity.

• Governance: On-shore business owns what and why; AI-GCC leadership owns how and who; centralized guardrails for risk, architecture, and financial metrics (including return on investment).

Anil has contributed significantly to the design and deployment of agentic AI workforce squads, aligning them to business outcomes and helping Fortune 500 enterprises make progress with their AI investments.

Value Drivers

According to Anil, the value drivers of AI-GCCs are:

• Speed and focus: Integrated cross-functional technology and operations teams work directly on your business goals, leading to faster project cycles and fewer handoffs.

• Structural cost advantage: Achieve reductions in total cost of ownership (TCO) between 45% and 65% by creating and managing agentic workforce organizations with highly optimized team structures and business processes.

• Talent access at scale: Tap into deep talent pools for AI, cybersecurity, and digital infrastructure and operations. In certain locations, the quality of new hires for specific (niche) skills can be better than what could be found locally for the same cost.

• IP and security control: Your data remains secure within company boundaries, minimizing third-party risk.

• Resilience: Multiple hubs allow for continuous operations and help diversify against geopolitical risks.

• AI at scale: AI-GCCs are especially well-suited for managing AI platforms, data governance, and model development.

High-Impact Use Cases

AI-GCCs deliver maximum value in areas such as:

• Digital and engineering: Product squads, cloud migrations, Platform/Site Reliability Engineering (SRE), Developer Experience (DevEx), and test automation.

• Data and AI: Lakehouse, Master Data Management (MDM), ML engineering, decisioning (pricing, fraud, churn), and knowledge assistants.

• Risk and cybersecurity: Threat intel, Know Your Customer (KYC) analytics, and Identity and Access Management (IAM) engineering.

• Middle and back office: Finance & accounting, procurement, HR, legal, and supply chain.

• Customer and growth ops: Sales and marketing, Customer Relationship Management (CRM), Revenue Growth Management (RGM), and Revenue Cycle Management (RCM).

In an increasingly volatile market environment, AI-GCCs may help enterprises reduce reliance on third-party vendors for AI development, thereby mitigating risks related to IP and security. As global regulations become stricter, keeping data processing and AI development within a captive GCC environment can offer better compliance than outsourcing to third-party service providers.

An AI-GCC is a strategic asset that could provide a competitive advantage and operational resilience while mitigating execution risk, resulting in substantive value creation for shareholders.