AI Safety Testing

AI safety testing is the practice of evaluating AI systems before and after deployment to find harmful behaviors, such as generating dangerous instructions, leaking private data, or producing biased or false outputs. For enterprises, it is the evidence base behind claims that a model is fit for its intended use, and regulators and customers increasingly ask to see it. Testing results can also shape contract terms, internal approval gates, and documentation required under frameworks like the EU AI Act.

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Corporate PolicyUK2026-10-26

UK's £600M AI Spend Expands Safety Institute Remit and Puts Autonomous Agents in Critical Infrastructure

The UK government has announced more than £600 million in AI-related spending, including £120 million for the AI Security Institute to test advanced AI systems for dangerous capabilities. A new National Cyber Shield will deploy autonomous AI agents across critical infrastructure, and a £70 million NERV Centre will use AI to detect vulnerabilities in real time. The package reshapes what enterprise compliance teams operating in the UK must anticipate from government AI oversight.

UK regulation critical infrastructure AI Security Institute autonomous agents dual-use AI AI safety testing vulnerability disclosure