AI Audit & Assurance Training Program

Who this program is for

• Auditors and assurance practitioners

  Learn how AI audit and assurance engagements are planned, conducted and reported under ISAE 3000.

• Internal audit teams

  Bring AI systems into your audit plan, test governance and controls, and evaluate the evidence behind claims made by your teams.

• Procurement and vendor management teams

  Evaluate an AI vendor’s documentation, test evidence and claims before procurement, and know what to ask for.

• Legal counsel

  Advise on AI risk and regulatory exposure with a working understanding of how the systems behave and where their risks arise.

• Risk and compliance professionals

  Assess AI risks and impacts in a structured way and recognize the governance obligations that recur across the major AI frameworks and regulations.

• AI governance leads

  Design oversight that holds up to independent scrutiny, and work with external auditors as an informed counterpart.

No coding is required, no advanced mathematics, and no prior audit experience.

What you will be able to do

• Follow a technical conversation with a development team and identify where the risk sits.

• Assess an AI system’s risks and impacts on the people it affects, and build a defensible risk register.

• Read a test report critically and judge whether the testing supports the claims being made.

• Evaluate AI governance structures and controls, and translate regulatory requirements into auditable criteria.

• Understand how an AI assurance engagement moves from scoping to evidence to a reported conclusion.

Curriculum: The five courses

1. 01

   AI & Machine Learning Foundations

   Follow a resume-screening system through its full development lifecycle, then build the vocabulary for everything from traditional machine learning to large language models and agentic systems. You learn the technical fluency to evaluate AI without becoming an engineer.

2. 02

   Algorithmic Risk & Impact Assessments

   Learn BABL AI’s structured method for identifying what could go wrong, who could be affected, and how serious the impact could be, aligned with ISO/IEC 42005. You apply it end to end to an LLM-based hiring tool, from stakeholder interviews to a prioritized risk register.

3. 03

   AI Testing & Evaluation Foundations

   Most testing is done by technical teams. Your job is to judge whether it is relevant, credible and complete. You learn to frame what a system’s results are valid for, interpret performance and fairness metrics, and know when to bring in a specialist.

4. 04

   AI Governance & Risk Management

   Examine who decides which risks are acceptable and who keeps watching once a system is live. The course covers governance structures, controls, third-party and agentic AI, and the EU AI Act, NIST AI RMF and ISO/IEC 42001. Every mechanism is viewed from both the organization’s side and the auditor’s.

5. 05

   AI Audit & Assurance

   Learn how AI audit and assurance engagements work under ISAE 3000: independence, criteria, evidence, materiality and assurance conclusions. You then follow a simplified NYC Local Law 144 bias audit from scoping through evidence review, claims verification and the final report.

How it works