AI assurance, with evidence a person can stand behind

It is the process of measuring, evaluating and communicating whether an AI system is trustworthy.

The UK government sets this out in its Introduction to AI assurance.

In practice, it produces evidence that a system works as intended and that people stay in control.

An AI audit is one assurance technique, usually a formal check against set criteria.

Assurance is broader and can include impact assessments, bias audits, performance testing and governance reviews.

We use whichever mix produces the evidence you need.

Most UK organisations are not required to buy it as such.

Existing law still applies to AI, including UK GDPR, the Equality Act 2010 and sector rules.

Assurance is how you show you meet them when AI is involved.

No.

We are not UKAS-accredited and we do not issue ISO/IEC 42001 certificates.

We prepare your controls and evidence so that a certification audit, a client questionnaire or a regulator’s question is easier to answer.

Yes.

In smaller organisations most AI risk sits in bought-in tools.

We review supplier evidence, your configuration and, above all, how your people check the outputs.

It depends on how many systems are in scope and how good your existing records are.

One well-documented system is a much smaller job than a spread of bought-in tools.

We agree scope and timing before we start.