Role-Based Programme
RB1427

AI-Powered Audit & Internal Controls

Intelligent Risk Assessment, Control Testing & Audit Analytics

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across audit planning, risk assessment, internal controls, control testing, evidence review, issue tracking, and audit reporting.
  • Use AI to analyse policies, process documentation, transactions, control matrices, audit evidence, exception data, prior findings, and management responses.
  • Build repeatable AI-assisted workflows for audit scoping, risk identification, sample analysis, control testing, issue documentation, remediation tracking, and reporting.
  • Apply AI to identify unusual transactions, recurring control failures, documentation gaps, emerging risks, overdue actions, and opportunities to strengthen control environments.
  • Design responsible AI-enabled Audit & Internal Controls workflows with appropriate controls for confidentiality, evidence integrity, professional judgement, explainability, auditability, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisAudit Analytics ToolsRisk & Control Management ToolsProcess Mining ToolsOCR & Data ExtractionReporting & Dashboard ToolsKnowledge Management AIWorkflow Automation

Who should attend

  • Internal Audit Managers
  • Internal Auditors
  • Senior Internal Auditors
  • Audit Analysts
  • Internal Controls Managers
  • Internal Controls Specialists
  • Risk & Controls Professionals
  • Financial Controllers
  • Finance Managers
  • Compliance Professionals
  • Governance, Risk & Compliance Professionals
  • SOX / Financial Controls Professionals
  • Process Assurance Professionals
  • Audit Analytics Professionals
  • Audit & Internal Controls Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of auditing, internal controls, finance, risk management, or compliance
  • Familiarity with business processes, control frameworks, audit evidence, risk registers, testing, and audit reporting
  • Basic proficiency with spreadsheets, documents, financial data, and workplace productivity applications
  • No previous AI course attendance required
  • No programming background required

TOC Modules

Concepts
  • Understanding Generative AI, analytical AI, Document AI, and audit automation
  • Mapping AI opportunities across audit planning, control testing, analytics, and reporting
  • Understanding AI assistance versus accountable audit judgement
  • Recognising confidentiality, evidence-quality, hallucination, and professional-judgement risks
Practical activities
  • Mapping an existing audit lifecycle
  • Comparing manual and AI-assisted audit activities
  • Creating an Audit & Controls AI opportunity matrix

Scenarios

Audit Planning to Issue Closure

Audit Universe → Risk Assessment → Scope → Risk-Control Matrix → Control Testing → Evidence Review → Findings → Management Action Plan → Follow-Up → Closure

Participants use AI-assisted techniques to manage a simulated internal audit from planning through risk assessment, testing, issue development, remediation tracking, and final closure while retaining professional conclusions with authorised audit personnel.

Transaction & Control Data to Continuous Assurance

Transactions + Control Results + Prior Findings + Process Data + Exception Logs → AI Analysis → Anomalies & Control Weaknesses → Priority Testing → Remediation Actions → Monitoring Dashboard → Audit Committee Review

Participants design an AI-enabled continuous assurance workflow that consolidates control and transaction data, identifies recurring exceptions and control weaknesses, automates appropriate monitoring activities, and strengthens audit visibility while retaining final risk and audit judgements with authorised professionals.

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