Role-Based Programme
RB1663

AI-Powered Enterprise Risk Management

Intelligent Risk Identification, Scenario Analysis & Strategic Risk Monitoring

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

Programme Objectives

  • Develop advanced capability to apply AI across enterprise risk identification, assessment, monitoring, scenario analysis, treatment planning, and executive reporting.
  • Use AI to analyse risk registers, strategic plans, policies, incidents, external developments, control information, KRIs, audit findings, and management reports.
  • Apply AI-assisted analytics to identify emerging risks, interconnected exposures, concentration areas, deteriorating indicators, and enterprise-wide risk themes.
  • Build repeatable AI-assisted workflows for risk assessments, risk-register maintenance, scenario analysis, action tracking, monitoring, and governance reporting.
  • Design responsible AI-enabled Enterprise Risk Management workflows with appropriate controls for confidentiality, explainability, accountability, data quality, auditability, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisEnterprise Risk AnalyticsScenario & Stress AnalysisRisk Register AnalyticsReporting & Dashboard ToolsKnowledge Management AIWorkflow Automation

Who should attend

  • Enterprise Risk Managers
  • Chief Risk Officers
  • Risk Managers
  • Enterprise Risk Analysts
  • Risk & Control Professionals
  • Operational Risk Professionals
  • Strategic Risk Professionals
  • Governance Professionals
  • Internal Auditors
  • Business Risk Managers
  • Risk Assurance Professionals
  • Risk Reporting Professionals
  • Business Continuity Professionals
  • Risk Governance Professionals
  • Enterprise Risk Management Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of enterprise risk, operational risk, governance, internal controls, audit, or business management
  • Familiarity with risk registers, risk assessments, KRIs, controls, mitigation plans, or management reporting
  • 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 the Enterprise Risk Management lifecycle
  • Understanding AI assistance versus risk-owner and management judgement
  • Recognising model limitations, confidentiality, explainability, and data-quality risks
Practical activities
  • Mapping an existing ERM process and identifying AI opportunities
  • Comparing manual and AI-assisted risk-management activities
  • Creating an ERM AI opportunity matrix based on value, complexity, and risk

Scenarios

Strategic Plan to Enterprise Risk Assessment

Strategic Objectives → Risk Identification → Risk Scoring → Interdependency Analysis → Risk Appetite Check → Mitigation Planning → KRIs → Executive Risk Report

Participants use AI-assisted techniques to analyse a simulated strategic plan, identify and assess enterprise risks, evaluate interdependencies and appetite alignment, and prepare a structured management-ready ERM report.

Enterprise Risk Register to Continuous Risk Monitoring Workflow

Risk Register + KRIs + Incidents + Emerging Risk Signals + Mitigation Status → AI Analysis → Priority Risks → Threshold Breaches → Automated Follow-Up → Dashboard → Board Reporting

Participants design an AI-enabled continuous ERM workflow that consolidates enterprise risk information, highlights emerging and interconnected risks, improves action tracking, and strengthens executive visibility while retaining all material risk decisions with authorised professionals.

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