Role-Based Programme
RB1691

AI-Powered IT Risk & Technology Audit

Intelligent Control Assessment, Audit Analytics & Technology Risk Governance

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

Programme Objectives

  • Develop advanced capability to apply AI across IT risk assessment, technology audits, IT control reviews, evidence analysis, issue tracking, and assurance reporting.
  • Use AI to analyse IT policies, system documentation, access records, change records, incident data, control evidence, audit findings, and technology-risk information.
  • Build repeatable AI-assisted workflows for audit planning, control assessment, evidence review, exception analysis, remediation tracking, and management reporting.
  • Apply AI to identify recurring technology risks, control weaknesses, anomalous patterns, documentation gaps, and areas requiring specialist investigation.
  • Design responsible AI-enabled IT Risk and Technology Audit workflows with appropriate controls for confidentiality, evidence integrity, security, explainability, auditability, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisIT Risk AnalyticsTechnology Audit AnalyticsControl Assessment ToolsEvidence AnalysisReporting & Dashboard ToolsWorkflow Automation

Who should attend

  • IT Risk Managers
  • IT Auditors
  • Technology Auditors
  • Technology Risk Professionals
  • Internal Auditors
  • Information Systems Auditors
  • IT Governance Professionals
  • GRC Professionals
  • Information Security Auditors
  • Risk & Control Analysts
  • Technology Control Professionals
  • IT Compliance Professionals
  • Digital Risk Professionals
  • Technology Assurance Professionals
  • IT Risk & Audit Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of IT risk, technology audit, internal controls, IT governance, or information systems
  • Familiarity with access controls, change management, IT operations, system documentation, audit evidence, or technology-risk assessments
  • Basic proficiency with spreadsheets, documents, data interpretation, 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 workflow automation
  • Mapping AI opportunities across IT risk, technology controls, audit, and assurance
  • Understanding AI assistance versus auditor judgement, technology expertise, and control ownership
  • Recognising confidentiality, security, hallucination, and model-risk concerns
Practical activities
  • Mapping an IT Risk and Technology Audit lifecycle and identifying AI opportunities
  • Comparing manual and AI-assisted technology assurance activities
  • Creating an AI opportunity matrix based on value, sensitivity, risk, and feasibility

Scenarios

Technology Environment to Risk-Based IT Audit

Technology Environment → IT Risk Identification → Control Mapping → Audit Scope → Evidence Review → Data Analytics → Findings → Remediation Plan → Executive Report

Participants use AI-assisted techniques to assess a simulated technology environment, identify key risks, review controls and evidence, analyse sample data, and prepare a structured IT audit report for management review.

IT Findings to Continuous Technology Assurance Workflow

Access Exceptions + Change Records + IT Incidents + Audit Findings + Remediation Data → AI Analysis → Risk Prioritisation → Automated Follow-Up → Dashboard → Management Reporting

Participants design an AI-enabled continuous assurance workflow that consolidates technology-risk signals, identifies recurring issues, tracks remediation, and improves management visibility while retaining all audit conclusions and high-risk technology decisions with authorised professionals.

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