Should You Build AI Capabilities Through a GCC? 

As organizations race to operationalize AI, many are reconsidering how and where they build the teams responsible for it. For companies evaluating a GCC AI strategy, the discussion centers on whether a Global Capability Center (GCC) can provide the talent, governance, and operational structure needed to support AI initiatives over time. 

Historically, GCCs were often associated with back-office support functions and cost efficiency initiatives. Today, many enterprises are using them to build engineering organizations, product development teams, cybersecurity functions, data platforms, and AI capabilities.  

For organizations facing an increasingly competitive AI talent market, the GCC model offers access to specialized talent, expanded operational capacity, and greater long-term control over critical capabilities. But that doesn’t automatically make it the right fit for every AI initiative. 

Why AI Is Driving New Interest in GCCs 

AI adoption is creating demand for highly specialized talent that remains difficult to find in many local markets. Machine learning engineers, AI platform engineers, data scientists, MLOps specialists, AI governance experts, and AI product managers are competing for the same limited hiring pool. 

According to the World Economic Forum’s 2025 Future of Jobs Report, advancements in AI and information processing are expected to be among the most transformative business trends through 2030, while AI and big data rank among the fastest-growing skill categories worldwide. Employers also expect 39% of workers’ core skills to change by 2030. 

OECD research also shows that demand for AI skills continues to outpace available supply across many developed economies, creating significant competition for qualified talent.  

As a result, organizations increasingly look beyond headquarters locations and traditional hiring markets when building AI teams. 

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RELATED: The Challenges and Opportunities of Building Global Teams 

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GCCs as AI Capability Hubs 

One reason GCCs are gaining momentum is that AI programs rarely succeed with a handful of isolated specialists. Effective AI organizations need cross-functional teams that can build, deploy, govern, maintain, and continuously improve AI solutions. 

That often requires: 

• AI engineers 
• Machine learning engineers 
• Data engineers 
• Data scientists 
• Product managers 
• Cloud architects 
• MLOps specialists 
• Cybersecurity professionals 
• AI governance and compliance experts 

Building all of those capabilities in one market can be difficult and expensive. 

By establishing a GCC, organizations can centralize AI expertise within a dedicated operating model aligned to long-term business objectives. A GCC can provide a dedicated structure for capability development, knowledge retention, and innovation across multiple initiatives. 

When Building AI Through a GCC Makes Sense 

While every organization’s AI strategy is different, certain business and workforce conditions make the GCC model particularly effective. 

Your AI Investments Span Multiple Business Functions 

Many organizations begin with isolated AI projects. Over time, demand for AI expands across departments, products, and operational functions. 

A GCC can provide the workforce structure and governance needed to support artificial intelligence initiatives across multiple business units while maintaining consistency in standards, tools, and processes. 

You Need Access to Larger AI Talent Pools 

Location remains one of the most important factors in AI workforce planning. 

Many leading GCC destinations have developed strong ecosystems for software engineering, advanced analytics, data science, and AI talent. Establishing a GCC in these regions can expand hiring capacity and provide access to specialized skills that may be difficult to find locally. 

Intellectual Property Protection Is a Priority 

AI initiatives often involve proprietary datasets, internal business processes, custom models, and sensitive intellectual property. 

Because GCCs operate as company-owned entities, organizations can maintain direct oversight of governance, security standards, compliance practices, and workforce management. 

AI Supports Core Business Operations 

Some companies use AI to improve efficiency. Others rely on AI to support software development, customer experiences, product innovation, supply chain operations, research activities, or business decision-making. 

Organizations that expect AI teams to become a permanent part of their operating model often see value in developing internal expertise through a GCC structure. 

When a GCC May Not Be the Right Approach 

A GCC can be a powerful workforce model, but its value depends on having the right scale, talent requirements, and organizational structure in place. 

Your AI Requirements Are Limited in Scope 

Organizations exploring a small number of artificial intelligence initiatives may not need the investment associated with establishing a GCC. 

In these situations, staff augmentation, consulting engagements, project-based delivery models, or blended workforce approaches may provide flexibility while AI priorities continue to develop. 

Leadership and Governance Structures Are Still Developing 

Launching a GCC requires local leadership, workforce planning, governance frameworks, operational oversight, and strong communication between locations. 

Without clear ownership and executive sponsorship, organizations may struggle to establish alignment across distributed teams. 

Workforce Planning Decisions Have Not Been Finalized 

Before establishing a GCC, leaders should determine which functions the center will support, how work will be managed, and what expertise must be developed internally. 

Organizations with clearly defined workforce objectives are typically better positioned to make informed GCC investment decisions. 

Is a GCC Right For Your AI Strategy? 

The answer depends on the role AI will play within your organization. 

Companies building enterprise-scale AI programs often need access to specialized talent, consistent governance, leadership oversight, and dedicated engineering capacity. A Global Capability Center can provide a structured environment for developing AI teams while supporting long-term ownership of critical capabilities. 

Organizations considering this model should evaluate talent availability, business objectives, operating structure, governance requirements, and the specific functions the GCC will support before making a decision. 

The strongest GCC strategies are built around clear workforce goals, well-defined ownership, and a practical understanding of how AI work will be executed across teams and locations. 

Build Your AI Team With Insight Global 

Building AI capabilities requires a workforce strategy that connects talent acquisition, workforce planning, delivery execution, and operational oversight. 

Insight Global helps organizations evaluate GCC opportunities, identify high-potential talent markets, build AI and data teams, establish leadership structures, and scale international workforce operations across key global regions. Whether you’re launching your first GCC or expanding an existing center, our experts are here to help.