Role-Based Programme
RB1662

AI-Powered Enterprise Risk Management

Smarter Risk Identification, Scenario Analysis & Strategic Risk Oversight

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

Programme Objectives

  • Apply AI across Enterprise Risk Management activities including risk identification, assessment, prioritisation, monitoring, treatment, and reporting.
  • Use AI-assisted techniques to analyse strategic, operational, financial, technology, compliance, and emerging risks more efficiently.
  • Develop structured workflows for risk registers, risk assessments, scenario analysis, KRIs, treatment plans, and management reporting.
  • Analyse enterprise-wide risk information to identify concentrations, interdependencies, emerging themes, deteriorating indicators, and areas requiring management attention.
  • Apply responsible AI practices covering confidentiality, data quality, assumptions, explainability, governance, and human judgement.

Tools covered

Generative AI AssistantsEnterprise Risk AnalyticsAI-Powered ResearchDocument IntelligenceSpreadsheet AnalysisScenario AnalysisRisk Register ManagementKey Risk IndicatorsManagement ReportingWorkflow Automation

Who should attend

  • Enterprise Risk Managers
  • Enterprise Risk Analysts
  • Risk Management Professionals
  • Chief Risk Office Professionals
  • Operational Risk Professionals
  • Strategic Risk Professionals
  • Internal Auditors
  • Governance, Risk & Compliance Professionals
  • Business Risk Managers
  • Risk & Control Professionals
  • Corporate Governance Professionals
  • Risk Reporting Professionals
  • Risk Assurance Professionals
  • Risk & Internal Audit Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of risk management, governance, controls, or business processes
  • Familiarity with risk registers, risk assessments, KRIs, or management reporting 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, automation, and their applications in ERM
  • Identifying AI opportunities across enterprise risk identification, assessment, monitoring, and reporting
  • Understanding AI assistance versus risk-owner and management accountability
  • Recognising limitations related to incomplete data, assumptions, bias, and explainability
Practical activities
  • Mapping the ERM lifecycle to AI-assisted activities
  • Identifying repetitive analytical and reporting tasks suitable for AI support
  • Comparing traditional and AI-assisted ERM workflows

Scenarios

Strategic Objective to Enterprise Risk Treatment Plan

Business Objective → AI-Assisted Risk Identification → Risk Assessment → Risk Appetite Review → Prioritisation → Treatment Options → Ownership → Management Review

Participants analyse a strategic business objective, identify relevant enterprise risks, assess exposure, compare treatment options, and prepare a structured risk-treatment plan.

Enterprise Risk Portfolio to Executive Risk Report

Risk Register + KRIs + Emerging Risks + Treatment Status → AI Analysis → Top Risks → Interdependencies → Escalations → Priority Actions → Executive Report

Participants consolidate enterprise-risk information, identify rising risks and interdependencies, highlight overdue actions and KRI breaches, and prepare a management-ready Enterprise Risk report.

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