Role-Based Programme
RB1426

AI-Powered Audit & Internal Controls

Smarter Risk Assessment, Control Testing & Audit Analytics

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Apply AI across Audit and Internal Controls activities including risk assessment, audit planning, control documentation, testing, exception analysis, and reporting.
  • Use AI-assisted techniques to analyse financial transactions, control evidence, policies, process documentation, reconciliations, and audit findings more efficiently.
  • Develop structured workflows for audit scoping, walkthroughs, control testing, issue documentation, remediation tracking, and follow-up.
  • Improve audit insight through AI-assisted anomaly analysis, control-gap identification, trend analysis, evidence organisation, and management reporting.
  • Apply responsible AI practices covering confidentiality, evidence integrity, professional judgement, auditability, data access, and human review.

Tools covered

Generative AI AssistantsAudit Data AnalysisInternal Control AnalysisDocument IntelligenceRisk Assessment SupportControl Testing SupportSpreadsheet AnalysisException AnalysisAudit ReportingWorkflow Automation

Who should attend

  • Internal Auditors
  • Audit Managers
  • Internal Control Professionals
  • Financial Controllers
  • Finance Managers
  • Risk & Control Analysts
  • SOX / Financial Control Professionals
  • Compliance Assurance Professionals
  • Process Control Specialists
  • Finance Governance Professionals
  • Accounting Managers
  • Audit Coordinators
  • Control Testing Professionals
  • Finance & Accounting Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of accounting, audit, internal controls, finance, or risk-management activities
  • Familiarity with financial processes, control testing, reconciliations, audit evidence, or process documentation is helpful
  • Basic spreadsheet and data-analysis skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, document intelligence, and automation in audit and control environments
  • Identifying AI applications across audit planning, testing, evidence review, exception analysis, and reporting
  • Understanding AI assistance versus auditor professional judgement and control-owner accountability
  • Recognising risks related to confidentiality, unsupported conclusions, incomplete evidence, and model error
Practical activities
  • Mapping the audit and internal-control lifecycle to AI-assisted opportunities
  • Identifying repetitive audit and control activities suitable for AI support
  • Comparing traditional and AI-assisted assurance workflows

Scenarios

Financial Process to Control Testing & Audit Finding

Process Walkthrough → Risk Identification → Control Mapping → AI-Assisted Test Design → Evidence Review → Exception Analysis → Auditor Validation → Finding → Remediation Plan

Participants review a simulated financial process, identify key risks and controls, perform structured control testing, analyse exceptions, and prepare an evidence-supported audit finding with remediation actions.

Audit & Control Data to Risk-Based Improvement Plan

Control Exceptions + Repeat Findings + Access Issues + Remediation Status + Transaction Anomalies → AI Analysis → Control Themes → Priority Risks → Improvement Actions → Management Report

Participants consolidate audit and control information, identify recurring control weaknesses and unresolved issues, and prepare a management-ready improvement plan with priorities, owners, deadlines, and follow-up measures.

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