Description

A focused course, tailored for you

Auditing the AI Control Environment for UK Assurance Engagements

A working playbook for Big4 audit and assurance teams asked to opine on an AI control environment inside a UK regulated client.

The audit section on AI controls is a paragraph. The engagement file needs working papers.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Senior managers and directors inside UK Big4 audit and assurance practices are being asked to extend the audit opinion across an AI control environment that nobody built audit assets for. The methodology team has guidance memos. The engagement team has clients with model inventories, vendor LLM dependencies, ICOFR scoping questions, and audit committee papers due in the next cycle. There is a gap between the methodology guidance and the working papers a senior manager needs in the file. That gap is what closes an engagement late, what triggers an EQR challenge, and what shows up as a finding when the regulator reviews audit quality. The course turns the guidance into engagement-ready working papers, walkthrough memos, test-of-one scripts, reliance memos, and the supporting narrative an EQR partner will sign without rework.

What you walk away with

Produce a walkthrough memo for an AI control that survives EQR review.
Run a defensible test of one over an AI model approval gate inside an engagement timeline.
Write the ICOFR scoping conclusion for an AI use case that ties to the audit file.
Draft an audit committee paragraph on AI controls that does not invite open questions.
Build the reliance memo a partner needs when audit cuts across a client AI control environment.

The 12 modules

Module 1. The AI use case inventory the audit file actually needs

Most client inventories are model risk inventories, not audit inventories. The audit file needs the use case, the control point, the reliance path, the data source, the financial reporting linkage if any, and the owner of evidence. Module one walks through converting a client model risk inventory into an audit-ready inventory, with the inventory worksheet that fits behind a walkthrough memo and lines up with the ICOFR scoping decision.

Module 2. ICOFR scoping for AI use cases without overstating reliance

Module two works through the scoping conclusion when an AI use case touches a financially significant process. The standard scoping questions read differently when the control is an approval gate over a model output. The module gives you the scoping narrative, the reliance framing, the in-scope and out-of-scope lines, and the precision question that EQR will challenge if it is missing.

Module 3. Walkthrough memos for AI controls a senior reviewer will sign

A walkthrough of an AI control is not a walkthrough of a model. It is a walkthrough of the human review, the approval gate, the change management discipline, and the monitoring loop. Module three is the walkthrough memo template with the four sections that need to be in the file, the questions to ask the control owner, and the worked example for an LLM-assisted customer correspondence control.

Module 4. Test of one for an AI model approval gate

The audit team needs a test that an engagement junior can execute against an approval gate over model output. Module four gives you the test script, the sample selection logic, the evidence list, the exception treatment, and the working paper format. It also covers the reperformance question when the gate is a human-in-the-loop check, and the no-deviation conclusion language that holds up in review.

Module 5. Change management evidence for vendor LLM dependencies

When a client depends on a vendor LLM, every vendor model update is a change event the audit needs to address. Module five gives you the change log walkthrough, the vendor SOC report reliance question, the supplementary inquiry letter to the vendor when SOC coverage falls short, and the exception narrative when an undisclosed update altered control output mid-period.

Module 6. Data lineage and input integrity working papers

AI controls rest on data the model consumed. Module six walks through the input integrity testing that audit needs to perform, the data lineage diagram that fits in the file, the cut-off question for training versus inference data, and the reliance treatment when the input data already sits behind a tested IT general control. Includes the lineage worksheet and the IT reliance memo it ties to.

Module 7. Monitoring controls, drift, and the period-end question

Many AI controls produce a model output that the operator reviews on a monitoring dashboard. Module seven addresses the audit treatment of model drift over the period, the monitoring exception log, the threshold escalation evidence, and the conclusion language for the period-end testing window. It includes the monitoring walkthrough memo and the file note for an undisclosed drift event.

Module 8. Audit committee reporting that does not invite open questions

The audit committee paragraph on AI controls is the public face of the engagement work. Module eight gives you three drafting patterns for different client maturities, the wording that names reliance without overcommitting, the wording for a scope limitation when client maturity is too low, and the example committee question and answer that a senior manager should prepare for ahead of the meeting.

Module 9. Reliance on the client model risk function

Most regulated UK clients have a model risk function with their own validation work. Module nine works through the reliance question, the documentation review that audit needs to perform, the gaps that disqualify reliance, and the reliance memo template. It covers what the second line owes the engagement and what the engagement still needs to do directly, with the worked example for a credit scoring use case.

Module 10. EU AI Act exposure for a UK client and the audit consequence

A UK client with EU customers or EU operations has EU AI Act obligations that flow into the audit, even when the client itself does not consider the regulation in scope. Module ten works through the exposure question, the controls expected by the regulation, the client representation letter language, and the audit response when the client is operating below the regulatory expectation.

Module 11. FCA, PRA, and ICO touchpoints inside a UK assurance engagement

Module eleven covers the audit touchpoints with FCA model risk supervisory expectations, PRA SS1/23 model risk principles, and ICO guidance on automated decision making. The module gives you the supervisory expectation map, the audit working paper that documents the client position against each expectation, and the management letter point template when a gap exists.

Module 12. The engagement close, EQR challenges, and the partner reliance memo

Module twelve closes the loop. It covers the engagement close checklist for AI control work, the EQR challenges most likely to surface and how to answer them in the file, the partner reliance memo that ties the audit opinion to the AI control conclusions, and the carry-forward note for the next year. Includes the EQR challenge log template and a worked partner memo for a mid-size UK regulated client.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

The audit committee paper carries one paragraph on AI controls and the next cycle will demand more.

The client has a model risk register but no audit inventory, and the file needs both.

A vendor LLM update broke the control narrative mid-period and the file has no exception note.

The EQR partner is going to ask what reliance was placed on second-line model validation work.

What you get with this course

Twelve written modules with the working paper templates referenced in each module.
Walkthrough memo template tailored to AI controls, with worked examples for three use case types.
Test of one script template for AI model approval gates, with sample selection guidance.
Reliance memo template covering vendor SOC reports, second-line model validation, and IT general controls.
ICOFR scoping conclusion language for AI use cases that survives EQR review.
Audit committee drafting patterns for three different client maturity levels.
EQR challenge log template with the ten most likely challenges and worked answers.
The hand-built implementation playbook tailored to your engagement context, delivered alongside course access.

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

Modules can be worked through in any order. Most senior managers work module one and module two first to anchor the engagement scope, then jump to the module that matches the next deliverable on the file.

Templates download as editable working files so they drop straight into the engagement file structure.

Before and after

Before

The audit file has guidance memos from the methodology team and a paragraph in the committee paper. The walkthrough is informal. The test of one is missing. The reliance memo is a placeholder. The EQR partner has questions the file does not answer.

After

The audit file has a walkthrough memo, a test of one, a reliance memo, an ICOFR scoping conclusion, a monitoring exception log, and an audit committee paragraph that names reliance without overcommitting. The EQR partner reads the section and signs.

What happens if you do not address this

Audit quality reviews this cycle will pull AI control coverage as a focus area. An engagement file that cannot evidence walkthroughs, tests of one, scoping conclusions, and reliance memos against AI controls will produce a finding. Findings of that shape attach to the senior manager and the engagement leader, not to the methodology team that issued the guidance.

Who it is for

A senior manager or director in a UK audit and assurance practice running an engagement where the client has live AI use cases that touch financial reporting controls or operational reliance. Comfortable with ISA, ISAE 3000, ICOFR scoping, walkthrough discipline, and EQR. Not a model risk specialist and not expected to be. Needs audit assets, not technical depth on the underlying models.

Who this is NOT for. Not for model risk specialists who are building the underlying validation framework. Not for data scientists who are constructing the model itself. Not for engagement leaders whose clients have no AI use cases in scope. The course assumes you are running an audit or assurance engagement and need the working papers, the memos, and the reliance narrative to support an opinion.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. Around six to nine hours across the twelve modules, plus the time to apply the templates to a live engagement. Most learners work through one module per evening and use the templates inside the working week.

Why $199 is the right number

Methodology-team guidance memos describe principles but rarely give engagement teams the working papers in editable form. Public regulatory guidance describes expectations but does not write your file for you. Generalist AI governance courses focus on the model risk function rather than the audit function. This course is written for the auditor sitting at the engagement, with the working papers that fit behind an audit opinion.

FAQ

Do I need a technical AI background?

No. The course assumes audit and assurance competence, not model engineering competence. The audit assets are written for senior managers and directors running engagements, not for data scientists.

Does this cover ISAE 3000 separate assurance engagements over AI?

The audit framing is primary, with cross-references to ISAE 3000 where a separate assurance engagement is the appropriate vehicle. Module eight and module twelve both include ISAE 3000 wording variants.

How is this different from a model risk validation course?

This is an audit course, not a validation course. The course teaches what audit needs in the file to opine on, or place reliance on, a model risk control environment. The validation work itself sits with the client second line.

Will the templates fit our firm methodology?

The templates are written to slot into a standard Big4 audit file structure. The implementation playbook is hand-built to your specific engagement context and reflects the methodology naming you actually use.

What if my engagement is not in financial services?

The templates are sector-neutral with worked examples spanning financial services, regulated industrials, and professional services. Module ten and module eleven contain the UK regulator-specific work; the rest applies wherever an audit opinion crosses an AI control environment.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.