Role-Based Programme
RB1664

AI-Powered Internal Audit

Smarter Audit Planning, Evidence Review & Assurance Reporting

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Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support Internal Audit activities across planning, risk assessment, control review, evidence analysis, documentation, and reporting.
  • Explore practical prompting techniques for audit planning, working papers, control assessments, evidence summaries, and audit observations.
  • Apply AI to organise audit information, analyse documents, structure findings, and prepare audit-ready working outputs.
  • Identify opportunities to improve audit efficiency, consistency, documentation quality, issue visibility, and follow-up.
  • Recognise confidentiality, evidence integrity, auditor independence, professional judgement, and human-review requirements when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Audit PlanningDocument IntelligenceSpreadsheet AnalysisAudit Evidence SummarisationControl ReviewIssue TrackingBasic Workflow Automation

Who should attend

  • Internal Auditors
  • Internal Audit Executives
  • Audit Analysts
  • Audit Managers
  • Senior Internal Auditors
  • Risk & Audit Professionals
  • Control Assurance Professionals
  • Governance Professionals
  • Process Assurance Professionals
  • Compliance Audit Professionals
  • Operational Auditors
  • Financial Auditors
  • Internal Audit Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of internal audit, risk, controls, or business processes
  • Familiarity with audit planning, evidence, working papers, or observations is helpful
  • Basic computer and spreadsheet skills
  • No AI or programming knowledge required
  • No previous Generative AI experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Internal Audit
  • Identifying AI applications across audit planning, fieldwork, documentation, testing support, and reporting
  • Understanding AI assistance versus auditor judgement, independence, and accountability
  • Recognising activities where evidence, professional scepticism, and human validation remain mandatory
Practical activities
  • Mapping common Internal Audit activities to potential AI applications
  • Comparing a traditional audit task with an AI-assisted approach

Scenarios

Business Process to Audit Plan

Business Process → AI-Assisted Risk Identification → Control Mapping → Audit Objectives → Evidence Requirements → Audit Plan

Participants use AI to analyse a sample process, identify potential risk areas, map relevant controls, and prepare a structured audit-planning summary for professional review.

Audit Evidence to Final Observation

Audit Evidence + Working Notes → AI Analysis → Condition → Criteria → Cause → Impact → Recommendation → Management Summary

Participants use AI to organise verified audit information into a structured observation and concise management summary while retaining final audit judgement with authorised Internal Audit professionals.

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