Three-quarters of UK IT leaders claim to have inadequate AI governance, yet 87% of them are already running agentic AI systems. This isn't a gap between aspiration and reality. This is organised negligence masquerading as pragmatism. For mid-market legal practices, insurers, asset managers and accountancy firms, this is the exact moment when the FCA, SRA, PRA and ICO will start treating AI governance failures as control failures. The fact that only 67% have an exit strategy — meaning a third would struggle to migrate away from a vendor if that vendor changed terms, raised prices or deprecated a model — suggests many firms don't actually understand what happens when their AI system becomes mission-critical and then breaks.

This pattern reveals something deeper than mere implementation laziness. Most vendor-led AI deployments — the ChatGPT wrappers, the Microsoft Copilot integrations bolted onto your existing stack, even some of the legal AI tools like Harvey and Luminance when deployed without proper governance — create a false sense of control. They're fast to stand up, easy to demo to partners, and impressive in month one. But they shift the real risk from technology to regulation. Under the EU AI Act, which will influence UK regulatory expectations, high-risk AI systems require documented risk management frameworks, human oversight logs, and clear audit trails. Most agentic deployments today have none of this. They're living on borrowed time.

Trovix's approach starts with a different assumption: governance isn't something you bolt on after deployment. It's built into how you acquire, implement and monitor AI from day one. This means understanding exactly what your AI system will touch — customer data, case decisions, claims decisions, investment recommendations — and then building controls that actually map to your regulatory obligations, not generic 'AI governance' templates. Tools like Trovix Watch exist precisely because regulatory environments are changing weekly, and firms need to know which governance rules actually apply to them before they've built the thing. If you deploy first and check compliance second, you're already ten steps behind.

What should a regulated firm actually do right now? First, audit what you've already deployed. Not just that it works, but whether you could explain its decisions to the FCA or SRA under pressure. Second, demand exit strategies as a contractual requirement before signing any new AI vendor agreements. Third, build governance into procurement — make your AI vendor prove they support audit logging, role-based access control, and decision explainability before you integrate. Fourth, don't confuse demos with deployment. The fact that a system can draft a contract paragraph or extract insurance claims data doesn't mean it's safe to rely on without human review workflows. Finally, treat agentic AI like you'd treat a junior fee-earner: it needs supervision, regular performance review, and clear boundaries about what it can decide alone versus what needs escalation. The firms that survive the next three years of regulatory scrutiny won't be the ones with the fanciest AI. They'll be the ones that documented their choices.

Source: Computer Weekly