AI Testing

Most AI systems reach launch having been tested only by people trying to make them work. Adversarial testing asks the other question: what happens when someone actively tries to make the system misbehave. This guide sets out what to test before go-live — how to scope the exercise and define harm in your own domain, the five attack classes that matter for business deployments, whether to run it internally, buy it in or automate it, how to score findings so severity cannot be renegotiated after the fact, which fixes actually hold, what the work costs in person-days and pounds, and the evidence pack that answers an enterprise security questionnaire and maps onto the EU AI Act, ISO 42001 and the NIST AI Risk Management Framework.