The gap between AI activity and AI outcomes has never been wider for GCC AI maturity today. Pilots are everywhere. Hackathons, prototypes, new tools, and new teams are being stood up across GCCs. But when leaders look for measurable enterprise impact, the picture gets harder to defend. Innovation pipelines break before they scale. Ideas stall at proof of concept. Work portfolios still lean heavily toward enablement, with limited depth in core model development, fine-tuning, or IP creation.
This is the moment GCCs have been building toward for a decade, and it is also the moment where the old playbook stops working. As enterprises move into an AI-first era, relevance is tied to outcomes, not experimentation. The question is no longer whether GCCs should invest in AI. It is whether they are positioned to own it.
If you run a GCC, this shift determines how central your center will be to enterprise strategy over the next five years. This report, developed by Zinnov in collaboration with Nasscom and Tiger Analytics, is built on 75+ surveys and interviews and three roundtable discussions with GCC Heads and technology leaders. It finds that:
This report introduces a structured framework to assess where GCC AI maturity stands today and what separates the centers pulling ahead from the ones stuck in pilot mode.
The GCCs pulling ahead are not the ones with the biggest teams. They are the ones that build leadership, capability, and foundational readiness in parallel, not in sequence. The real question is: is your GCC positioned to own the AI agenda, or is it still waiting to be handed one?
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