Training module
Auditing AI Risk & Impact Management
Evaluate harm, impact and risk reasoning, intended use alignment, and decision traceability in ISO/IEC 42001
Does your audit move beyond paperwork to defensible, traceable AI risk and impact decisions?
AI risk and impact management is credible when it clearly connects intended use, affected stakeholders, and documented decisions to real controls and oversight. This module helps auditors test that chain and recognise where reasoning, traceability, or documentation breaks down in practice.
Overview
What this module is about
In ISO/IEC 42001 audits, weak AI risk and impact management rarely fails because an organisation used the wrong framework. It fails because the organisation cannot show a coherent line from intended use and stakeholders to impact reasoning, risk decisions, and documented acceptance of trade-offs. This creates false assurance: the system looks controlled on paper, while key harms, misuses, and operational realities remain unaddressed.
This standard-specific auditing module shows how to audit the quality of reasoning and documentation behind AI risk and impact decisions, without re-teaching generic risk methods or generic audit craft. It is designed to stand on its own in the ISO/IEC 42001 auditor pathway and is applicable to internal auditors and third-party auditors, including certification-body and independent assurance contexts.
Audience
Who it is for
Management system implementers and coordinators
Executives and department heads accountable for management system performance
Those responsible for processes, policies, assets, risks and controls
Auditors seeking insight into management-side practice, not audit technique
Consultants working on management system design, governance or improvement
Decision supportIs this module for you?
It is a good fit if you…
seek to audit the quality of AI risk and impact reasoning.
are aiming to judge alignment between intended use, impacts, and decisions.
focus on traceability from risk reasoning to documented controls.
are prepared to test whether decisions hold up under real use conditions.
expect to strengthen audit conclusions on AI risk governance.
It may not be the best fit if you…
prefer to design AI risk frameworks or impact assessment methods.
are looking for guidance on harm analysis or ethical risk modelling.
focus primarily on managing or mitigating AI risks yourself.
do not intend to audit AI risk and impact management under ISO/IEC 42001.
What to bring
This module assumes auditors can already apply core audit evidence and judgement concepts and are familiar with management system basics. It does not teach generic audit craft or generic risk methodology.
Helpful background includes:
Practical ability to evaluate evidence, sampling rationale, and professional judgement
General understanding of how management systems use documented information to support governance decisions
Agenda
What is taught
5 parts01AI risk and impact management in an ISO/IEC 42001 audit
What auditors judge: coherence, traceability, and operational credibility of AI risk and impact decisions. Scope boundary: no generic risk frameworks, no audit-craft re-teaching.
02Testing harm and impact reasoning
Assesses whether harms and impacts are defined in a usable, decision-ready way (who/what is affected, how, why it matters), and whether severity, likelihood, and uncertainty are treated consistently and transparently.
03Intended use integrity and stakeholder alignment
Tests alignment between intended and actual use, including scope drift, misuse paths, and silent expansion via configuration or integration. Verifies that affected stakeholders and obligations were substantively considered, not just listed.
04Decision documentation quality
Evaluates decision records for rationale, trade-offs, approvals, and residual risk acceptance. Checks cross-document consistency across impact assessments, risk decisions, controls, monitoring triggers, and incident learning.
05Evidence trails, sampling focus, and red flags
Identifies where evidence actually sits in governance routines and operational records. Flags template compliance, post-hoc rationales, unowned residual risks, and undocumented trade-offs.
Outcomes
Learning outcomes
01
Evaluate whether harm/impact reasoning is specific, complete enough for decisions, and consistent across artefacts
02
Test traceability from intended use and stakeholder considerations to impact assessment, risk decisions, and controls
03
Assess whether risk and impact decisions are documented in a way that supports accountability and later review
Identify and prioritise evidence sources that demonstrate real operation (not just planned intent)
Recognise common ISO/IEC 42001 risk/impact audit red flags that indicate false assurance
Define focused audit tests for decision quality without substituting for generic audit planning or interviewing techniques
Materials
The content and the assessment
Written module
The full content in writing, complete in itself. Videos are recorded for parts of it as an alternative way through, and the written module always carries everything.
Exercises
Graded work on the case organisation's own registers: structured answers checked against the encoded case, written answers scored against a rubric traced to it, with a trainer holding the final word on every assessed item.
On completion
The assessed exercises must be passed before the certificate is issued.
Scheduling
No public run of Auditing AI Risk & Impact Management is scheduled at the moment. Tell us you are interested and we will let you know when the next one opens, or discuss running it in-house.
Module facts
- Module ID
- HAM-AI-A-01
- Discipline
- Artificial Intelligence
- Part of tracks
- Management System Auditor
Case organisation
All modules share one company
Each module enters the company at a particular point in its history and finds it as that history has left it.
Northstar Integrated Services AG is a group headquartered in Zurich, operating in six European countries, with about 1,350 employees at the end of 2025. It provides digital operations platforms and managed operational services to regulated organisations in healthcare, the public sector and industrial services. Founded in 2008 as a field-operations firm serving business customers, it had about twenty-five employees when its first regulated customer, a hospital group, required documented decisions, named accountability and evidence on request. It moved into the platform business in 2016 and in 2024 acquired an operating business in Poland and the Czech Republic, whose legal entity continues inside the group.
Linked registers
Organisation and people, roles, risks, objectives, policies, documents and records, communications, findings, audits and reviews, interested parties, processes
Records, not summaries
The evidence sits in the registers and documents where a real organisation would keep it.
A history
The company has a timeline from 2008, so a structure can be examined before and after it changed.
More than one legal entity
A Swiss parent company and an acquired subsidiary in Poland and the Czech Republic, with customers in several jurisdictions
Why it matters
Judgement develops on material that is incomplete and partly contradictory, as it is in practice. Northstar is built that way on purpose. Because modules enter its history at different points, a governance structure can be seen while it is built, when it is outgrown and when it is rebuilt.
Delivery & dates
How this module reaches you
Delivered live online, combining conceptual framing, discussion, case work and direct interaction with the trainer. In-house and contextualised delivery is available on request.
No public run is scheduled at the moment. Most modules run on request as well as on the public calendar, so tell us the timing you need.
Want this module scheduled?
We will tell you when the next run is scheduled, or run this module in-house with your own case material.
Not sure it is the right module?
Describe your context in a short message and we will tell you honestly.