“For global enterprises, that fragmentation alone creates operational headaches — not because they’re unwilling to comply, but because each regulation defines concepts like transparency, usage, explainability, and accountability in slightly different ways,” he says. “What works in North America doesn’t always work across the EU.”
Thomas recommends that organizations adopt a suite of governance controls and systems as they deploy AI. In many cases, a major problem is that AI adoption has been driven by individual employees using personal productivity tools, creating a fragmented deployment approach.
“While powerful for specific tasks, these tools were never designed for the complexities of regulated, enterprise-wide deployment,” he says. “They lack centralized governance, operate in silos, and make it nearly impossible to ensure consistency, track data provenance, or manage risk at scale.”