Role-Based Programme
RB1425

AI-Powered Audit & Internal Controls

Smarter Control Testing, Risk Analysis & Audit Reporting

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Audit and Internal Controls across planning, control assessment, evidence review, testing, exception analysis, and reporting.
  • Apply AI-assisted techniques to analyse financial records, control documentation, audit evidence, transactions, and operational data.
  • Use structured prompting for audit planning, control testing, risk identification, evidence summarisation, and audit reporting.
  • Explore AI-supported approaches for identifying control gaps, recurring exceptions, unusual transactions, and areas requiring further audit attention.
  • Build responsible AI-assisted audit workflows while maintaining independence, evidence integrity, confidentiality, traceability, and professional judgement.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Financial Data AnalysisAudit Planning AIInternal Control AnalysisEvidence ReviewRisk & Exception AnalysisReporting & Workflow Automation

Who should attend

  • Internal Auditors
  • Audit Executives
  • Internal Control Professionals
  • Finance Control Professionals
  • Risk & Control Analysts
  • Financial Auditors
  • Compliance Analysts
  • Finance Analysts
  • Process Control Professionals
  • Governance Professionals
  • SOX / Internal Controls Professionals
  • Finance Managers
  • Internal Audit Managers
  • Audit & Internal Controls Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of audit, accounting, finance, or internal-control concepts
  • Familiarity with financial records, process controls, audit evidence, reconciliations, or compliance reviews 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 and control activities
  • Identifying AI applications across audit planning, evidence review, control testing, exception analysis, and reporting
  • Understanding AI assistance versus auditor and control-owner judgement
  • Recognising limitations such as hallucinations, incomplete evidence, bias, and unsupported audit conclusions
Practical activities
  • Mapping a typical Audit & Internal Controls workflow
  • Identifying repetitive and information-intensive activities suitable for AI assistance
  • Comparing a traditional audit task with an AI-assisted approach

Scenarios

Financial Process to Internal Control Review

Process Description → AI-Assisted Risk Identification → Control Mapping → Evidence Review → Control Testing → Exceptions → Audit Observation

Participants use AI to analyse a sample financial process, map risks to controls, review evidence, and prepare structured audit observations for professional validation.

Transaction Data to Audit Findings & Management Report

Transaction Data + Control Evidence + Exceptions → AI Analysis → Unusual Patterns → Follow-Up Testing → Verified Findings → Management Actions → Audit Report

Participants use AI to analyse sample financial and control information, identify areas requiring investigation, and prepare a management-ready audit summary without delegating audit conclusions to AI.

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