The structural choice for CXM GCCs - Everest Group Research Portal

In the first blog in this series, we established that Global Capability Centers (GCCs) are becoming more important in Customer Experience Management (CXM) because the technology stack has shifted from a one-time platform choice to a continuously governed operating capability. In the second, we examined how Artificial Intelligence (AI) is redrawing the in-house-versus-outsourced boundary, making ownership of orchestration and governance more consequential.

The next question follows naturally, if GCCs are gaining relevance and their mandate is widening, what kind of GCC model is best suited to support high-maturity CXM?

That question is best answered through a maturity lens, not a binary choice between dedicated and multi-tower GCCs. Both models can deliver value: one through service-control excellence, the other through enterprise coordination, but the comparison starts with understanding how CX maturity in GCCs evolves.

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Evolution of CX maturity in GCCs

CX in GCCs is no longer about scale. The real differentiator now is how mature the CX operating model is, which reflects how far a GCC has moved from handling service demand to shaping customer outcomes through integrated capabilities. Exhibit 1 demonstrates that GCCs typically evolve from channel execution to broader customer operations ownership.

Exhibit 1
Evolution of CX maturity in GCCs

The shift is not just greater scale or more channels, but a change in purpose. Lower-maturity models create value mainly through delivery efficiency. Higher-maturity models create value by reducing friction across journeys, connecting front- and back-office execution, and improving customer outcomes through faster, more coordinated change.

Reaching high maturity depends not only on capability build but increasingly on GCC structure. The maturity inflection point is when a GCC shifts from a service-delivery arm to an enterprise capability for customer operations. In practice, high-maturity CX GCCs are distinguished by:

a unified case and workflow backbone
governed knowledge operations rather than static knowledge publishing
strong telemetry across interactions, workflows, exceptions, and outcomes
integrated exception handling across front, middle, and back office
proactive customer updates rather than reactive contact handling
faster iteration across markets through reusable operating patterns and release discipline

Importantly, these capabilities cut across functions, not just front-office CX. That raises a key question: where should these cross-functional capabilities sit within a GCC?

How high maturity manifests across dedicated and multi-tower GCCs

High maturity looks different across GCC models. Dedicated CXM GCCs typically express maturity through clearer accountability and faster standardization, while multi-tower GCCs express it through deeper cross-functional integration and greater end-to-end transformation potential. Exhibit 2 shows both models can achieve high maturity, but with different trade-offs.

Exhibit 2
Dedicated CXM GCC vs. multi-tower GCC

A dedicated CXM GCC usually reaches maturity through tighter service governance, stronger control over QA, WFM, knowledge, and support operations, and faster standardization across channels and markets. A multi-tower GCC reaches maturity through closer integration across CX, data, workflow, automation, platforms, and back-office operations, which gives it more leverage when the source of customer friction sits outside the CX layer itself.

Dedicated models often create clearer ownership and quicker operational discipline but can struggle to address upstream root causes when key levers sit in product, risk, and operations teams. Multi-tower models create broader transformation headroom, but only if governance prevents diffuse ownership and slow cross-functional decision-making.

These dynamics help explain why the center of gravity in many enterprises is shifting toward multi-tower models.

Why CXM increasingly defaults to multi-tower GCCs

In many enterprises, CXM increasingly sits inside multi-tower GCCs because customer outcomes now depend on shared enterprise capabilities. Several reasons drive this shift:

GCCs have evolved. Many are no longer single-function support hubs. They increasingly combine technology, operations, automation, data, and digital transformation under one structure. In this context, CXM naturally becomes one tower within a broader enterprise capability model
Enterprises seek customer-operations integration. The goal is not only to run channels efficiently but to close the gap between front-office interactions and back-office resolution. Multi-tower GCCs are often better positioned to support that end-to-end operating model. For example, in industries such as airlines, where disruption management requires coordination across service, crew, and operations, and utilities, customer service must be tightly linked with field operations
Customer friction often originates beyond the contact center. Poor service experiences are frequently triggered by breakdowns in order flows, claims handling, account updates, exception management, fulfillment, or field operations. Resolving customer issues depends on workflows, data, and core systems. Improving customer outcomes therefore requires tighter linkage between customer-facing teams and the operational functions that ultimately resolve the issue. For example, in banking, dispute resolution depends on coordination across payments, risks, and operations, while in retail, order and returns management directly shape customer experiences
AI and automation scale best on shared foundations. Capabilities such as intelligent routing, agent assist, proactive notifications, semantic search, and decision support depend on common data, workflow, and platform layers. For example, in telecom, linking customer care with network data enables proactive issue resolution; in insurance, claims automation depends on integrating CX with core policy and data systems

These factors do not eliminate the role of dedicated CXM GCCs, but they explain the center of gravity is shifting.

How multi-tower GCCs can supercharge digital transformation in the era of AI?

AI increases the value of multi-tower GCCs because transformation centers on embedding intelligence into workflows and decisions. In that environment, multi-tower GCCs act as the internal engine that connects AI ambition to enterprise execution. Exhibit 3 illustrates the real advantage of the multi-tower model lies in its ability to connect intelligence to execution.

Exhibit 3

How multi-tower GCCs can supercharge digital transformation in the era of AI

Shared foundations make AI easier to scale. Cross-functional proximity speeds up change. Stronger telemetry improves control and optimization. Broader enterprise linkage allows AI to redesign customer operations, not just improve isolated interactions.

This shift does not make providers less relevant. Instead, it changes their role. As enterprises increasingly use GCCs to anchor orchestration, governance, and operating integration, providers remain important as capability accelerators, bringing specialist talent, platform expertise, and execution capacity where speed and scale are needed.

Bottom line

The next phase of CXM maturity will not be defined by how well enterprises manage channels. It will be defined by how effectively they connect customer interactions to the wider system of workflows, decisions, data, automation, and resolutions that shape customer outcomes.

Dedicated CXM GCCs remain highly effective where enterprises need sharper accountability, faster standardization, and deeper functional specialization in customer operations. However, as CXM depends more on integrated workflows, AI-enabled decisioning, and end-to-end operational coordination, multi-tower GCCs matter more now because they create the structural conditions for broader transformation.

If you enjoyed this blog, check out, How global capability centers are driving transformation: The evolving landscape – Everest Group Research Portal, which delves deeper into another topic relating to GCCs.

If you’d like to discuss AI, GCCs, or CXM, please contact David Rickard ([email protected]), Dhruv Khosla ([email protected]), Anish Agarwal ([email protected]), or Rakshit Hooda ([email protected]).