AI Governance Fails Without Compute Infrastructure, Experts Warn

Global AI governance frameworks focus heavily on ethics, safety, and policy alignment, but largely overlook the computing infrastructure needed to put those policies into practice. Most frameworks assume nations already have access to high-performance compute, reliable data pipelines, and skilled operators — an assumption that does not hold for the majority of the world. The real AI divide is not about access to AI models but about the infrastructure required to run, monitor, and maintain them safely. Initiatives that prioritize training and workshops without providing compute access are considered insufficient, as operational capability requires hardware, secure environments, and long-term maintenance funding. Experts argue that bridging the AI divide demands treating infrastructure — including regional compute hubs, sovereign capacity, and energy planning — as a core governance priority rather than an afterthought.