In a landscape where data privacy regulations are increasingly stringent and AI models demand access to vast, diverse datasets, traditional security frameworks fall short. And from multinational collaboration to internal data silos, the need for a new, data-centric approach to AI governance is paramount.
Whether collaborating across internal teams, external partners or new markets, organizations must ensure that their sensitive data remains protected and compliant with local laws — and traditional security frameworks aren’t built to…