Every new GCC today starts with an AI-first mandate. Digital-first, AI-first operating models aren't a differentiator anymore, they're the baseline. For centers that have been around a while, the harder question is different: how do you transform existing platforms, teams, and ways of working so AI moves from a few pilots to real, enterprise-scale impact?

Across the industry, GCCs are effectively sorting into three generations, each carrying a different set of advantages and a different set of problems. Knowing which generation a center belongs to, and what that means for its leadership, is now essential to planning what comes next.

1. Built Without the Baggage

Centers being set up today start with a real structural advantage, and it's worth being precise about what that advantage actually is. It isn't better technology. The same models, tools, and platforms are available to every center, new or old. The advantage is the absence of legacy: no inherited processes, no org structures built for a pre-AI world, no workflows that assume a large team is needed for work AI can now handle.

These centers don't bolt AI onto an existing way of working. They design the way of working around it from the start. Workforce plans, team structures, delivery processes, all assume AI is part of the team from day one. This is exactly the position a fast-growing SMB or mid-market company is in when it sets up its first GCC through a build-operate-transfer model: there's no old operating model to unwind, no legacy headcount plan to defend. The center gets built AI-native the first time, not retrofitted into it three years later.

2. The Closing Window of Transition

Centers set up over the last five years sit in a genuinely useful middle position. They have operational momentum, established teams, and credibility with their global organization, but their ways of working haven't yet hardened to the point where change becomes too expensive to attempt.

These centers are moving fast, reworking headcount plans, rethinking team structures, and shifting toward AI-led ways of working before those earlier decisions get costly to reverse. Their advantage is timing, and it's a shrinking one. The longer a center settles into its current shape, the more expensive it gets to change, which is why the strongest centers in this group are acting now rather than waiting for more certainty.

3. Legacy Centers and the Weight of Scale

The longest-established centers carry real strengths: scale, mature teams, deep institutional knowledge, and years of earned trust with headquarters. Those advantages matter, and they'll continue to matter. But these centers also face the heaviest lift. A significant share of their work will be directly affected by AI, and operating models built for a different era need a genuine reset, not a minor tune-up.

The hardest part of that reset has almost nothing to do with technology. It means changing how thousands of people work, how teams are structured, how performance gets measured, and how careers progress. That kind of change management is among the toughest programs any enterprise can run, and it deserves the same investment and leadership attention as any major transformation. Centers that treat it as a side effect of adopting AI will struggle. Centers that treat it as the main program will come out stronger.

4. AI Doesn't Fix a Model. It Amplifies It.

One principle runs through all three generations. AI doesn't repair a flawed operating model, it amplifies whatever model it's handed. Applied to a well-designed center, it compounds the advantage. Applied to an outdated one, it compounds the friction. The real divide between these generations isn't when they were built. It's how much of their operating model is ready for AI-driven ways of working.

That's a useful test for any leadership team to sit with. If you were building your center today, from a blank page, how much of it would you build the same way? The gap between that answer and your current reality is the transformation agenda. New entrants get to skip this question. Everyone else has to answer it, and the centers moving fastest are answering it on their own terms, rather than waiting for it to be forced on them.