Glossary

AI risk assessment

An AI risk assessment is the structured process of identifying, weighing and controlling the risks a specific AI system could create — to people, data, decisions or the business — before it's deployed and on an ongoing basis afterwards.

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Part of our topic guide on AI Governance & Data Strategy.

An AI risk assessment is the structured process of identifying, weighing and controlling the risks a specific AI system could create — to people, data, decisions or the business — before it's deployed and on an ongoing basis afterwards. It asks what could go wrong, how likely that is, how bad it would be, and what you'll do about it — for one system, one use case, at a time.

Why it matters

Get this wrong and the damage rarely shows up as a dramatic failure — it shows up as a model quietly making bad decisions nobody's checking on: a screening tool that skews unfair, a forecasting model fed on data that's gone stale, a chatbot that says something it shouldn't to a customer. In our experience, the bigger risk most organisations carry isn't a rogue system — it's a system nobody assessed properly because nobody on the team had the skill to do it. That's the pattern behind the wider adoption problem: most AI initiatives stall not because the tools are weak, but because the people around them can't yet spot, size and manage the risk. A risk assessment forces that judgement to happen on purpose, before the system is live, instead of by accident after something breaks.

How it works

A workable AI risk assessment usually covers:

  • What the system does — the specific task, the data it uses, and who or what it affects.
  • What could go wrong — inaccurate or biased outputs, data misuse, security gaps, over-reliance on the tool, or unclear accountability when it makes a bad call.
  • How likely and how serious — a plain rating of probability and impact, not a guess dressed up as precision.
  • What controls reduce it — human review at the right points, testing before rollout, clear limits on what the system is allowed to decide alone.
  • Who owns it — a named person accountable for the assessment and for revisiting it as the system, its data, or its use changes.

The UK has no single statutory "AI Act" — assessment obligations instead sit with existing sector regulators (the ICO for data protection, and others by sector) and with voluntary frameworks organisations choose to adopt, such as ISO/IEC 42001 (an international AI management system standard) or the NIST AI Risk Management Framework. Where an organisation's AI systems or outputs touch the EU market, the EU AI Act can also apply and typically expects a risk assessment as standard practice. Either way, the assessment itself is a practical discipline, not just a compliance form — and it's one most teams have to build the muscle for, not buy off the shelf.