The instinctive response to regulatory fragmentation is localisation.
California requires something? Add a California control.
Europe introduces another obligation? Build an EU process.
Another jurisdiction follows? Add another layer.
Eventually, the organisation has accumulated a compliance architecture that mirrors the complexity of regulation itself.
That is expensive and strategically fragile.
The growing tension between US federal AI policy and state-level requirements offers an early warning.
Different jurisdictions may disagree on transparency, high-risk systems, discrimination, accountability and even how aggressively AI should be regulated.
A multinational enterprise cannot eliminate those differences.
But it can decide where complexity lives.
The stronger architecture is not:
Regulation → new control → new workflow.
It is:
Enterprise risk → common control → regulatory mapping.
Build a defensible control spine around enduring obligations: inventory, risk classification, accountability, testing, human oversight, incident management, evidence and lifecycle monitoring.
Then map jurisdiction-specific requirements onto that spine.
If one regulation requires an impact assessment, determine which existing controls satisfy it and where additional evidence is needed.
If another introduces transparency obligations, extend the relevant control rather than creating another governance system.
This distinction matters because regulations will continue changing faster than enterprise operating models should.
The strategic objective isn’t one global policy pretending legal differences don’t exist.
Nor is it dozens of local AI governance systems.
It is one control architecture capable of absorbing regulatory variation.
That changes the board-level question.
Don’t ask:
How many AI regulations must we comply with?
Ask:
How much of our governance architecture remains defensible when the regulation changes?
The organisations that solve that problem won’t merely become more compliant.
They’ll make regulatory change cheaper to absorb.