Review an incident involving AI output and identify the assurance gap that allowed it.

Assess the impact of a proposed AI use on the people it affects.

Design fairness requirements for a system and the evidence they require.

Establish transparency and explanation requirements for a system.

Advise on a use that is permitted but should not proceed.

Design the route by which an affected person can challenge an AI-influenced decision.

Assess the labour and skill effects of an AI deployment.

Apply the obligations of a regulated or professional context to AI use.

Review an AI-related incident for the ethical failure, not only the technical one.

Design an AI feature so that untrusted content cannot cause privileged action.

Threat model an AI feature, identifying assets, entry points and adversaries.

Design controls that limit what a system can do when its instructions are compromised.

Evaluate the effectiveness of guardrails and output controls under realistic conditions.

Diagnose how sensitive data reached a prompt, context window, log or output.

Evaluate supply chain risk in models, tools, extensions and connectors.

Design least-privilege access for systems acting on behalf of people.

Resolve an incident in which an AI system was the vector, and identify the control that failed.

Advise on unsanctioned AI use, addressing the need that produced it.