GCC Cost Architecture in 2026: AI-Led Models vs Vendors
7 min read
Two numbers define the AI story inside GCCs in 2026. The first is 83 percent. The second is 58 percent. The EY India GCC Pulse Survey 2025 reports that 83 percent of GCCs invest in generative AI and 58 percent invest in agentic AI. Another 29 percent plan to scale agentic AI over the next year. Pilots are giving way to production. The survey was conducted from August to October 2025 and covers the centres that average about 800 employees.
The industry numbers validate this momentum. NASSCOM report mentions 2,117 GCCs employ 2.36 million professionals and generate $98.4 billion in revenue. The revenue nearly matches the $100 billion figure that NASSCOM has projected to reach by 2030.
Gartner expects worldwide AI spending to reach $2.59 trillion in 2026, which is up by 47 percent from 2025. Every dollar of it raises a hard question.
Does a cost model built on headcount continues to make sense?
This article sets out a better way to think about GCC cost architecture. It compares AI-led GCC models with traditional vendor models. It also offers a practical framework for leaders who must decide where each workload belongs.
Why does the traditional GCC cost model break down in 2026?
The old model was built around the number of seats, where the GCC would take over work from an outside vendor team and do it at a lower cost per person. Finance teams would check the headcount and attrition to judge whether the arrangement was working, and clarity was there.
However, that model would miss a lot of details. Like, it did not account for what slow decisions had cost the business, or for what happens when data is scattered across teams and systems. A vendor contract might look cheap on the invoice. The chances are the company might pay the hidden costs in many other ways, namely, rework, delays, and the time people spend fixing problems. These were and are some essential issues that a closer, better-connected GCC team can identify and solve early.
Guess what, AI has changed the arithmetic. Gartner expects worldwide AI spending to reach $2.59 trillion in 2026, which is a 47 percent rise over 2025. Gartner also expects that agentic AI spending will cross chatbot spending by 2027. In the present scenario, software performs work that once needed entire team strength. Hence, a cost model built on seats cannot price that shift.
Budget pressure adds urgency. Gartner has projected a global IT spending of $6.37 trillion in 2026. It also notes that inflation and rising hardware costs will strain technology budgets. CFOs need proof of return.
Forrester observes that boards are moving AI from hype to hard numbers. It further expects that CFOs will join AI deals earlier. Therefore, a GCC must justify itself through outcomes. Leaders need a fresh outlook to meet these expectations and keep strategy intact.
What do traditional vendors still do well?
Vendors deliver speed. They bring ready teams and proven playbooks, which will enable a company to launch a program/project within weeks. That value is real.
They also carry deep cross-industry exposure, as they have seen many failure patterns and can help clients avoid them.
However, the weakness sits in the commercial model. Most vendor contracts reward effort. They bill for hours and people. But AI reduces the effort a task needs. Say, a vendor that bills for effort earns less when AI improves. That conflict rarely appears in a proposal.
How does AI reshape GCC cost architecture?
Cost architecture describes where money goes and what it buys. AI changes that structure in several places.
Let’s start with ownership. A GCC owns its data and its talent. That ownership lets AI gains compound. A vendor team improves a process once and moves to the next client. A GCC embeds the improvement permanently.
Next, consider the talent mix. Industry reports claim that talent for AI and ML within India’s GCCs has nearly doubled from 122,000 in 2023 to an estimated 250,000 in 2026. It implies, these engineers are building agents that absorb routine work, optimizing the costs.
Then consider pricing logic. A seat carries a fixed monthly cost. After a build an AI agent carries a marginal cost close to zero. So, the leaders who fund the build gain a durable advantage.
Now, consider the speed of learning. Every automated workflow produces data that trains the next agent. A GCC that owns the loop improves faster through each quarter.
Where should enterprises place each workload: GCC, vendor or automation?
We recommend a simple rule, which is place each workload according to two questions.
How much strategic value does the work carry, and how ready is it for AI integration?
High value, high AI readiness: This work belongs in the GCC. Product engineering and data platforms are good examples. Considering they shape the company’s core products and benefit the most when the gains from AI stay in-house and scale over time.
Low value, lower AI readiness: This work belongs with vendors. Legacy maintenance and fixed-term projects fit here, since they need steady execution and flexible capacity rather than deep ownership.
High value, lower AI readiness: This work needs investment before anything else happens. The work matters, but the data and processes are not yet in shape for AI. So, leaders should build the data foundation first and gradually scale.
Low value, high AI readiness: This work belongs with automation. Neither a GCC nor a vendor should assign people to these tasks, because software can handle them at close to zero marginal cost.
This rule gives the CFO clarity to decide the investments and cash flow. It gives the CHRO clarity on the talent strategy. It also stops teams from moving broken processes offshore and expecting that it would get fixed.
What is a Next-Gen GCC?
NASSCOM reports that nearly 75 percent of India GCCs can grow into portfolio or transformation hubs within five years. Almost half already handle advanced work at a similar or higher share than headquarters. These centres own global products and business outcomes.
The next generation goes further. It runs on an AI-first operating model. It measures value created instead of heads employed. It governs AI with discipline. A next-gen GCC builds that discipline from day one. It also grows talent internally through a clear learning path.
Such a centre treats cost as an output of good design. It never treats cost as the design goal.
The question for 2026 is no longer GCC or vendor. The question is which model creates a compounding value. Leaders who rethink cost architecture now will own their AI advantage.
Enablr stands ready to help enterprises build the next generation of GCCs.
How does Enablr help enterprises build next-gen GCCs?
Enablr acts as a catalyst for enterprises that want to build next-gen GCCs. We begin with cost architecture, not real estate. Our teams build the full economics of a GCC against the vendor alternative. We include AI productivity in the business case from the first day.
Next, we design the operating model and the talent strategy. Then, governance follows as a part of the same plan. In this way, we help leaders choose the right location and the right ecosystem for the GCC.
Enablr builds centres that grow in value. A centre that opens with a small team can mature and scale into a transformation hub.
Talk to Enablr about your GCC cost architecture
<section class="faq-section"> <div class="faq-inner"> <div class="faq-side fi v"> <div class="eyebrow">FAQs</div> <h2 class="sh2">Related questions</h2> <p class="sp"> Straight answers on GCC cost models, what vendors still do well, AI investment, and how to build a next-gen centre. </p> <a href="/contact" class="btn-primary">Talk to Us →</a> </div> <div class="faq-list fi v"> <!-- FAQ 1 --> <div class="faq-item"> <div class="faq-q" onclick="toggleFaq(this)" aria-expanded="false"> <span class="faq-q-text">Why does a headcount-based GCC cost model fall short in 2026?</span> <span class="faq-toggle"> <svg viewBox="0 0 24 24"> <line x1="12" y1="5" x2="12" y2="19"></line> <line x1="5" y1="12" x2="19" y2="12"></line> </svg> </span> </div> <div class="faq-a"> <div class="faq-a-inner"> A seat-based model counts people and attrition, but it misses the cost of slow decisions and scattered data. It also cannot price the shift to AI, where software now does work that once needed whole teams. A GCC is better judged by the outcomes it delivers than by the number of heads it employs. </div> </div> </div> <!-- FAQ 2 --> <div class="faq-item"> <div class="faq-q" onclick="toggleFaq(this)" aria-expanded="false"> <span class="faq-q-text">What do traditional vendors still do well?</span> <span class="faq-toggle"> <svg viewBox="0 0 24 24"> <line x1="12" y1="5" x2="12" y2="19"></line> <line x1="5" y1="12" x2="19" y2="12"></line> </svg> </span> </div> <div class="faq-a"> <div class="faq-a-inner"> Vendors deliver speed. They bring ready teams and proven playbooks, so a company can launch a project within weeks, and their cross-industry experience helps clients avoid common failures. The weakness is the commercial model: most contracts bill for hours and people, so a vendor earns less as AI reduces the effort a task needs. </div> </div> </div> <!-- FAQ 3 --> <div class="faq-item"> <div class="faq-q" onclick="toggleFaq(this)" aria-expanded="false"> <span class="faq-q-text">How much are GCCs investing in AI?</span> <span class="faq-toggle"> <svg viewBox="0 0 24 24"> <line x1="12" y1="5" x2="12" y2="19"></line> <line x1="5" y1="12" x2="19" y2="12"></line> </svg> </span> </div> <div class="faq-a"> <div class="faq-a-inner"> The EY India GCC Pulse Survey 2025 reports that 83 percent of GCCs invest in generative AI and 58 percent invest in agentic AI. Another 29 percent plan to scale agentic AI over the next year, which shows that pilots are giving way to production. </div> </div> </div> <!-- FAQ 4 --> <div class="faq-item"> <div class="faq-q" onclick="toggleFaq(this)" aria-expanded="false"> <span class="faq-q-text">What is the first step in building a next-gen GCC?</span> <span class="faq-toggle"> <svg viewBox="0 0 24 24"> <line x1="12" y1="5" x2="12" y2="19"></line> <line x1="5" y1="12" x2="19" y2="12"></line> </svg> </span> </div> <div class="faq-a"> <div class="faq-a-inner"> Start with cost architecture, not real estate. Build the full economics of the GCC against the vendor alternative, include AI productivity in the business case from day one, and then decide which workloads belong in the centre. Operating model, talent strategy, and governance should follow as part of the same plan. </div> </div> </div> <!-- FAQ 5 --> <div class="faq-item"> <div class="faq-q" onclick="toggleFaq(this)" aria-expanded="false"> <span class="faq-q-text">Can a GCC grow into a transformation hub?</span> <span class="faq-toggle"> <svg viewBox="0 0 24 24"> <line x1="12" y1="5" x2="12" y2="19"></line> <line x1="5" y1="12" x2="19" y2="12"></line> </svg> </span> </div> <div class="faq-a"> <div class="faq-a-inner"> Yes. NASSCOM reports that nearly 75 percent of India GCCs can grow into portfolio or transformation hubs within five years. A centre that opens with a small team can mature and scale as it takes on global products and business outcomes, especially when it runs on an AI-first operating model and grows talent internally through a clear learning path. </div> </div> </div> </div> </div> </section> <style> :root { --faq-ink: #12151c; --faq-body: #5a616f; --faq-line: #e6e8ec; --faq-accent: #4b3df6; --faq-bg: #fbfbfd; } * { box-sizing: border-box; } .faq-section { background: var(--faq-bg); font-family: 'Inter', 'Helvetica Neue', Arial, sans-serif; padding: 80px 24px; } .faq-inner { max-width: 1120px; margin: 0 auto; display: grid; grid-template-columns: 340px 1fr; gap: 64px; align-items: start; } .faq-side { position: sticky; top: 40px; } .eyebrow { font-size: 12px; font-weight: 700; letter-spacing: 1.5px; text-transform: uppercase; color: var(--faq-accent); margin-bottom: 14px; } .sh2 { margin: 0 0 12px; font-size: 32px; line-height: 1.15; letter-spacing: -1px; font-weight: 650; color: var(--faq-ink); } .sp { margin: 0 0 20px; font-size: 14px; line-height: 1.6; color: var(--faq-body); max-width: 38ch; } .btn-primary { display: inline-flex; align-items: center; gap: 6px; background: var(--faq-ink); color: #fff; text-decoration: none; font-size: 14px; font-weight: 600; padding: 12px 22px; border-radius: 999px; transition: background .2s ease, transform .2s ease; } .btn-primary:hover { background: var(--faq-accent); transform: translateY(-1px); } .faq-list { display: flex; flex-direction: column; } .faq-item { border-bottom: 1px solid var(--faq-line); } .faq-item:first-child { border-top: 1px solid var(--faq-line); } .faq-q { display: flex; align-items: center; justify-content: space-between; gap: 24px; padding: 22px 4px; cursor: pointer; user-select: none; } .faq-q-text { font-size: 16px; font-weight: 560; color: var(--faq-ink); line-height: 1.4; transition: color .2s ease; } .faq-q:hover .faq-q-text { color: var(--faq-accent); } .faq-toggle { flex: 0 0 auto; width: 28px; height: 28px; border-radius: 50%; border: 1px solid var(--faq-line); display: flex; align-items: center; justify-content: center; transition: background .25s ease, border-color .25s ease, transform .3s ease; } .faq-toggle svg { width: 14px; height: 14px; stroke: var(--faq-ink); stroke-width: 2; fill: none; transition: stroke .25s ease; } .faq-q[aria-expanded="true"] .faq-toggle { background: var(--faq-ink); border-color: var(--faq-ink); transform: rotate(135deg); } .faq-q[aria-expanded="true"] .faq-toggle svg { stroke: #fff; } .faq-q[aria-expanded="true"] .faq-q-text { color: var(--faq-ink); font-weight: 650; } .faq-a { display: grid; grid-template-rows: 0fr; transition: grid-template-rows .35s ease; } .faq-a-inner { overflow: hidden; font-size: 14.5px; line-height: 1.7; color: var(--faq-body); padding-right: 52px; } .faq-a-inner a { color: var(--faq-accent); font-weight: 600; text-decoration: underline; text-underline-offset: 3px; text-decoration-thickness: 1px; transition: color .2s ease; } .faq-a-inner a:hover { color: var(--faq-ink); } .faq-item.open .faq-a { grid-template-rows: 1fr; } .faq-item.open .faq-a-inner { padding-bottom: 22px; } .fi.v { animation: faqFadeIn .5s ease both; } @keyframes faqFadeIn { from { opacity: 0; transform: translateY(10px); } to { opacity: 1; transform: translateY(0); } } @media (prefers-reduced-motion: reduce) { .faq-a, .faq-toggle, .fi.v { transition: none; animation: none; } } @media (max-width: 900px) { .faq-inner { grid-template-columns: 1fr; gap: 32px; } .faq-side { position: static; } } @media (max-width: 520px) { .faq-section { padding: 56px 18px; } .sh2 { font-size: 26px; } .faq-q-text { font-size: 15px; } .faq-a-inner { padding-right: 0; } } </style> <script> function toggleFaq(qEl) { var item = qEl.closest('.faq-item'); var isOpen = item.classList.contains('open'); document.querySelectorAll('.faq-item.open').forEach(function (openItem) { if (openItem !== item) { openItem.classList.remove('open'); openItem.querySelector('.faq-q').setAttribute('aria-expanded', 'false'); } }); if (isOpen) { item.classList.remove('open'); qEl.setAttribute('aria-expanded', 'false'); } else { item.classList.add('open'); qEl.setAttribute('aria-expanded', 'true'); } } </script>
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