Britixo · Practical product and service guidance
AI Compliance Insights
Practical questions for AI governance: system inventories, risk reviews, evidence, monitoring and accountable human decisions.
01
Separate the system from the claim
An AI product description is not evidence of how your organisation uses it. Begin with the specific workflow, data, suppliers, users and decisions. A useful review records what the system is allowed to do, what requires human approval and where uncertainty remains. This makes later technical and governance decisions easier to explain.
02
Build a connected evidence trail
Keep the inventory, risk assessment, evaluation results, access decisions and incident records connected. A policy document and a monitoring dashboard serve different purposes: one defines expectations, while the other helps show what happened. Both need an owner, a review date and a clear relationship to the deployed system.
03
Turn findings into changes
Prioritise findings by their consequence for people and operations. Define the action, reviewer and acceptance evidence before changing a model or workflow. The linked pages explore the software side of risk management, audit evidence and telemetry. They support discovery and implementation planning; they do not certify a deployment or replace a context-specific assessment.