Role-Based Programme
RB1665

AI-Powered Internal Audit

Smarter Audit Planning, Evidence Analysis & Reporting

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Internal Audit activities across planning, risk assessment, evidence review, testing, issue analysis, and reporting.
  • Apply AI-assisted techniques to analyse policies, procedures, process information, audit evidence, findings, and action trackers.
  • Use structured prompting for audit planning, checklist creation, evidence summarisation, control review, and audit-report drafting.
  • Explore AI-supported approaches for identifying recurring issues, evidence gaps, control weaknesses, and overdue remediation actions.
  • Build responsible AI-assisted Internal Audit workflows while maintaining independence, confidentiality, evidence integrity, professional scepticism, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisAudit Planning AIEvidence AnalysisAudit Reporting AIWorkflow Automation

Who should attend

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

Prerequisites & Participant Readiness

  • Basic understanding of Internal Audit, Risk Management, or business controls
  • Familiarity with audit plans, policies, procedures, evidence, controls, or audit reports is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Internal Audit
  • Identifying AI applications across audit planning, fieldwork, evidence review, issue analysis, and reporting
  • Understanding AI assistance versus auditor judgement, independence, and accountability
  • Recognising limitations such as hallucinations, incomplete evidence, bias, and unsupported conclusions
Practical activities
  • Mapping a typical Internal Audit lifecycle
  • Identifying repetitive and information-intensive audit activities suitable for AI assistance
  • Comparing a traditional audit task with an AI-assisted approach

Scenarios

Business Process to Risk-Based Audit Plan

Business Process → AI-Assisted Risk Identification → Audit Scope → Controls → Audit Procedures → Evidence Requirements → Audit Plan

Participants use AI to analyse a sample business process, identify key risks and controls, and prepare a structured risk-based audit plan while retaining all final audit judgements with authorised auditors.

Audit Evidence to Finding & Follow-Up

Audit Evidence → Exception Review → Control Analysis → Root-Cause Questions → Audit Finding → Recommendation → Action Tracker → Management Report

Participants use AI to organise sample audit evidence, develop supported findings and recommendations, and create a concise follow-up report for management review.

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