There is a tendency in many organisations to treat artificial intelligence as purely a technology issue — something for the IT department or the data science team to manage. This is a mistake, and it's one that compliance professionals are uniquely positioned to correct.
The regulatory landscape is shifting fast
The EU AI Act is now in force, establishing the world's first comprehensive legal framework for artificial intelligence. It introduces risk-based classification of AI systems, mandatory conformity assessments for high-risk applications, and transparency obligations that reach well beyond the technology teams building these tools. For any organisation deploying AI that affects individuals — whether in hiring, credit decisions, customer service, or compliance monitoring itself — regulatory obligations are no longer theoretical.
In the UK, the regulatory approach is sector-specific rather than horizontal, but the direction of travel is clear. The FCA, ICO, and other regulators are all signalling increased scrutiny of how organisations use AI and automated decision-making. Compliance professionals who wait for prescriptive rules before engaging with AI governance will find themselves playing catch-up.
Why compliance professionals should lead this work
AI governance requires exactly the skills that compliance professionals already have: risk assessment, policy development, regulatory interpretation, and the ability to translate complex obligations into practical organisational controls. The challenge is not technical — it's about ensuring that AI systems are deployed within a framework of accountability, transparency, and proportionate risk management.
This means developing AI-specific policies, conducting impact assessments that go beyond data protection to consider fairness and bias, ensuring board-level visibility of AI risk, and building monitoring processes that can identify problems before they become regulatory incidents. These are governance challenges, not engineering challenges.
The practical starting point
If your organisation is using AI tools — and almost every organisation is, whether they've formally acknowledged it or not — the starting point is an inventory. What AI systems are in use? What decisions do they influence? What data do they process? Who is accountable for their performance and compliance?
Most organisations cannot answer these questions today, and that gap represents a material governance risk. The compliance function doesn't need to become a team of AI engineers. It needs to apply the same rigorous, risk-based thinking to AI that it applies to every other area of regulatory obligation. The organisations that get this right early will have a significant advantage as regulatory expectations continue to crystallise.