AI Audit & Assurance (NIST AI RMF)

What you will be able to do

• You will be able to scope an AI assurance engagement using the NIST AI RMF and the Generative AI Profile as audit criteria.
• You will be able to assess each trustworthiness characteristic and translate it into testable, evidence-backed audit objectives.
• You will be able to evaluate AI evidence artifacts such as model cards, datasheets, and test reports for sufficiency and reliability.
• You will be able to design and interpret bias and robustness tests, including the limits of what each test can and cannot prove.
• You will be able to write clear, condition-criteria-cause-effect audit findings supported by reproducible evidence.
• You will be able to assemble a structured AI assurance report with an objective opinion, scope, limitations, and prioritized recommendations.
• You will be able to distinguish between attestation, certification, and advisory assurance and set realistic expectations for each.

What is inside

4 modules, 8 lessons. Each module ends in a graded quiz and most carry an assignment.

1. 01

   Auditing AI Against the NIST AI RMF

   An AI audit is only as good as its criteria. This module shows how to turn the NIST AI RMF and its Generative AI Profile into concrete, testable audit criteria, and how to scope an engagement so the opinion you give is one you can actually defend.

   2 lessons · 5 quiz questions

2. 02

   Trustworthiness Characteristics and Evidence

   The AI RMF defines what a trustworthy AI system looks like. This module turns those seven characteristics into audit objectives and teaches you how to evaluate the artifacts that prove them: model cards, datasheets, and test results.

   2 lessons · 5 quiz questions · assignment

3. 03

   Bias and Robustness Testing

   Trustworthiness claims are only credible if they are tested. This module shows how bias and robustness testing actually work, how to design or review them, and just as importantly, the limits of what each test can prove.

   2 lessons · 5 quiz questions

4. 04

   Writing Findings and the Assurance Report

   Testing produces raw observations; assurance produces a clear, defensible conclusion. This module teaches the craft of writing AI audit findings and assembling a complete assurance report with a properly worded opinion, scope, and limitations.

   2 lessons · 5 quiz questions · assignment