From BOT to BOTT: Why the transfer was never the finish line
By Singaravelu Ekambaram, SVP and Global Head of Delivery, Americas at Cognizant
For two decades, Build-Operate-Transfer was the dominant logic for GCC establishment and it worked. It gave enterprises a structured, lower-risk entry into India: capability built by a partner with the expertise, operated long enough to prove stability, then handed over. Clean sequencing, clear milestones, defined exit.
The problem is not with the model. It is with what the model assumed: that transfer was the destination.
What we are seeing across GCC engagements today is that the most consequential work begins after the handover. Centers that were set up to run defined delivery functions are now being asked to own global product platforms, drive AI industrialisation at enterprise scale, and contribute directly to top-line outcomes. A framework built around arriving at independence does not adequately equip a center to do any of that. It gets you to a starting line and calls it a finish.
This is why we think about it differently — as Build, Operate, Transform, Transfer: BOTT. The sequence matters, but so does what it signals. Transform is not a phase that follows operate. It is continuous, embedded from the start, and it does not stop at transfer.
Transformation, in this sense, is not process improvement or cost optimization. It is a center becoming something structurally different from what it was built as: a capacity provider becoming a capability provider, an execution center becoming an innovation center, labor arbitrage giving way to digital leverage, process support giving way to business outcomes, traditional operations becoming AI-powered ones. The center that receives the handover should be materially more capable — strategically, technically, organisationally — than the one that was originally built.
The Transform Imperative
What does Transform require in practice? Five things the original BOT model did not architect for.
Process Transformation. BOT optimized for stability — repeatable, predictable, audited once and left alone. BOTT treats process as something to keep re-engineering: lean operating practices and intelligent workflows that improve continuously rather than getting fixed at handover.
Technology Transformation. AI integration as an ongoing operating discipline, not a project. The EY India GCC Intelligence Report 2026 found that 58% of GCCs are already investing in agentic AI, with a further 29% planning to do so within a year. It also means building capabilities the original model never needed — AgentOps to deploy, monitor, and govern agents in production, and FinOps to prove the value they generate.
Talent Transformation. BOT hiring built for execution; BOTT hiring builds for ownership. Cognizant’s own approach centers on two archetypes: the Frontier Certified Engineer, who builds and governs AI systems, and the Frontier Business Operator, who translates them into business outcomes. That shift starts with the hiring profile: BOT rewarded service managers, QA leads, and process engineers; BOTT calls for product architects, ML-ops leaders, and platform owners. The original model transferred people alone; BOTT transfers people and the AI agents the partner has built into the operation, each carrying its own governance handover.
Operating Model Transformation. AI at scale is an organisational question before it’s a technology one. It requires cross-functional, product-aligned teams with genuine end-to-end ownership — not siloed specialists, not centers of excellence advising from the margins — and governance that evolves with adoption instead of being retrofitted after the fact.
AI Transformation. Governance can’t be a compliance layer added after deployment. It has to be designed into how AI-driven processes get built in the first place — from the workflow’s first line of code through how outcomes get measured and owned.
What This Means for How You Engage
The original promise of GCCs was cost efficiency. What’s emerging now is different: enterprise intelligence — the ability to combine people, data, processes, and AI into an operating model that works at scale, not just access to AI itself.
For enterprise leaders currently evaluating a GCC engagement or mid-way through one, the practical question is where planning attention is concentrated. Governance structures for the transfer matter. The continuous investment in transformation — capability depth, AI maturity, operating model evolution — matters more, and it needs to start earlier than most engagement models currently assume.
The enterprises extracting the most value from their GCCs are not those that execute the smoothest transfer. They are those that use the partnership to build a center capable of owning its next chapter before the transfer happens — and capable of writing the chapter after that on its own.
BOTT reframes the question from “when do we hand this over?” to a more ambitious mandate: build capabilities, operate at scale, transform with AI, transfer knowledge, and continuously reinvent.