How to create a global capability center that acts as a strategic driver for business growth
When a global capability center (GCC) underdelivers, the diagnosis is usually people: wrong hires, wrong scope, not enough seniority. It’s rarely the honest answer. More often the center was wired like a branch office and asked to behave like a headquarters.
The GCC has evolved from an offshore cost play to a strategic extension of HQ, owning engineering, product, and, increasingly, the AI build. This is no longer solely for the Fortune 500. Leaner centers of 50–200 people, as well as ‘GCC-as-a-service’ and managed models, put it within reach of many US midmarket companies. Demand for AI is accelerating this trend further. India alone now has more than 2,000 GCCs, generating $98.4 billion in revenue in the fiscal year 2026.
“A GCC is never about cost effectiveness, it’s about tapping the best talent to take enterprises to the next technological orbit. The GCC model is shifting to intellectual arbitrage,” says Murali Krishnan, AVP & Head of Business – Enterprise Network at Tata Communications.
With lower barriers to entry, midmarket companies are looking to tap into this opportunity. However, this size of business tends to carry a domestic, branch-office playbook into a GCC and wire it accordingly. While that network was good enough for a branch office, it actively limits what a GCC can do and can limit their return on investment.
Midmarket companies looking to tap into this opportunity face a structural mismatch. Existing networks connect offices to a data center inside one country, with bandwidth sized accordingly. A GCC introduces AI workloads across several clouds and two continents, and the branch office network reaches its design limits.
What AI-driven workflows demand from the network
The growth in GCCs, alongside the rapid adoption of AI, has increased strain on the network, driving demand for high-performance connectivity across geographies. Model training, data-pipeline engineering, analytics platforms, and real-time inference are all areas where GCCs are taking a growing share of enterprise work.
“If the network is not a focus, your AI is not going to be giving you the bang for your buck,” Krishnan continues. “The network wasn’t the priority and treated like a commodity until recently. But now with AI spearheading, the network king is back where it deserves.”
Non-AI era networks were not built to handle the traffic and throughput required for these workloads. Training runs move terabytes between storage and compute, pipelines pull data continuously across regions and clouds, and inference must return in milliseconds.
AI workloads are expensive – GPUs can easily run into a few thousand dollars an hour. If left waiting for data to come through, it can leave GPUs standing idle, undermining the economic case of the whole GCC.
This is where most existing WAN architectures fall short. They were built on an MPLS-era model: traffic backhauled to a central hub, static routing, no awareness of the application riding on top, and bandwidth priced to discourage the exact data movement AI depends on.
The design assumes the systems that matter live at HQ. In a GCC, running AI workloads across several clouds, they don’t. It forces traffic through a hub-and-spoke network, adding latency precisely where there is no tolerance for it.
For a midmarket company the gap is wider. Existing networks are typically domestic and not meant for cross-border, cloud-to-cloud traffic, with no large network team to absorb the difference.
Managing complexity at scale
Few GCCs run in a single environment. A typical setup spans multiple clouds (AWS, Azure, GCP), several regions, and a roster of vendors: connectivity providers, colocation facilities, hyperscalers, and managed-service partners.
“Global enterprises coming into India face real problems handling multi-vendor contracts – user islands from one vendor, WAN islands from another, cloud islands from a third,” explains Krishnan. What’s missing, in his view, is a single partner who owns the outcome across those vendors – someone who can guide an enterprise through that complexity rather than leaving it to stitch the pieces together itself. “Enterprises must identify a sherpa to deliver a unified network – one that’s composite, compliant, and delivers certainty,” he continues.
Each addition is individually defensible. Every new cloud, region or vendor adds an interface to manage, a contract to hold accountable, and a seam where performance can quietly degrade.
The real cost of that sprawl is visibility. When workloads move across on-premises systems, several clouds and a wide-area network stitched together from different providers, no single view shows what is happening end-to-end.
Latency creeps in at the handoffs between environments, and without unified observability, the team cannot see where.
The pattern is well documented: 80% of US multi-cloud enterprises report cross-border connectivity and compliance challenges in the APAC region, where most GCC capacity sits.
WACKER Chemie AG, a major German multinational chemical and biotechnology corporation, is building a new GCC in Pune, India. The company’s head of connectivity says that scaling is one of the hardest parts of the move from a closed, “centric” network to a hybrid one where cloud is fully integrated, with security an equal concern, since every new environment widens the surface to protect.
“All services must be available 24/7 and also the requirements for the bandwidth, performance, and latencies are increasing from day to day,” explains Johannes Sautter, WACKER’s Head of Connectivity and Colocation Services. “We need to have good partners who are flexible and can react to our demands.”
What an integrated GCC operating model looks like
When connectivity is treated as overhead, the GCC inherits whatever capability the network has.
It runs as a second-tier satellite: capable, but always a half-step behind headquarters, pushed toward asynchronous, lower-value work because the real-time, data-heavy tasks never quite perform.
Treating connectivity as infrastructure reverses the equation. The network that was a constraint becomes the thing that lets the GCC operate at headquarters standards: real-time collaboration, shared development environments, multi-cloud workloads, and AI pipelines, all performing as though the team were sat down the hall.
“Infrastructure has to be discussed during the initial business case development,” explains Greg Wade, an independent strategic advisor who advises multinationals on GCC strategy and development. “It’s unfortunate that many organizations treat connectivity and infrastructure as implementation details.”
For midmarket companies, this is what separates a GCC that scales from one that stalls. Get the network right early, and the center can take on more valuable work as it matures, moving from support to engineering, and eventually to the AI and product capability that justified the investment in the first place.
The decision must be made about what the GCC will become, not what it is on day one. As Wade says: “Build that GCC for what you want three years from now, not the one you’re launching today.”
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