Role-Based Programme
RB1702

AI for Risk & Internal Audit

Smarter Risk Assessment, Audit Analytics & Control Assurance

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

Programme Objectives

  • Apply AI across Risk and Internal Audit activities including risk identification, audit planning, control assessment, evidence review, testing, documentation, and reporting.
  • Use AI-assisted techniques to analyse policies, procedures, transactions, audit evidence, risk registers, and control information more efficiently.
  • Develop structured workflows for risk assessment, audit scoping, testing, issue identification, root-cause analysis, and corrective-action tracking.
  • Analyse structured and unstructured data to identify anomalies, trends, recurring control issues, emerging risks, and potential areas requiring deeper review.
  • Apply responsible AI practices covering confidentiality, audit independence, evidence validation, professional judgement, data protection, and human oversight.

Tools covered

Generative AI AssistantsAI-Powered ResearchDocument IntelligenceSpreadsheet & Data AnalysisRisk AnalyticsControl Testing SupportAudit DocumentationAnomaly DetectionReporting AssistanceWorkflow Automation

Who should attend

  • Internal Auditors
  • Internal Audit Managers
  • Risk Management Professionals
  • Enterprise Risk Professionals
  • Operational Risk Professionals
  • Audit Executives
  • Risk Analysts
  • Controls & Assurance Professionals
  • Governance, Risk & Compliance Professionals
  • Process Risk Professionals
  • Internal Control Professionals
  • Compliance Assurance Professionals
  • Audit Team Leads
  • Risk & Internal Audit Managers

Prerequisites & Participant Readiness

  • Working knowledge of Risk Management, Internal Audit, controls, or assurance activities
  • Familiarity with risk registers, audit programmes, policies, process documents, or control testing 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, machine learning, and automation in Risk and Audit
  • Identifying AI applications across risk assessment, audit planning, testing, documentation, and reporting
  • Understanding AI assistance versus auditor judgement, independence, and accountability
  • Recognising high-risk activities where AI outputs require stronger validation and professional review
Practical activities
  • Mapping the Risk and Internal Audit lifecycle to AI-assisted opportunities
  • Identifying repetitive and information-intensive audit activities suitable for AI support
  • Comparing traditional and AI-assisted audit workflows

Scenarios

Risk Assessment to Audit Finding

Business Process → AI-Assisted Risk Identification → Control Mapping → Audit Scope → Evidence Review → Testing → Exceptions → Root Cause → Audit Finding

Participants use AI to analyse a sample business process, identify risks and controls, design audit testing, evaluate evidence, and develop a structured finding while retaining auditor judgement over all conclusions.

Transaction Data to Risk & Audit Management Report

Transaction Dataset → AI-Assisted Analysis → Anomalies & Exceptions → Risk Categorisation → Investigation Questions → Findings → Action Tracker → Executive Report

Participants analyse sample transactional information, identify unusual patterns, separate potential exceptions from verified issues, and prepare a management-ready Internal Audit report with clear actions, owners, and follow-up requirements.

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