Role-Based Programme
RB1661

AI-Powered Enterprise Risk Management

Smarter Risk Identification, Scenario Analysis & Strategic Monitoring

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Duration
8 Hours
Level
Basic
Delivery
Instructor-Led
Format
Workshop

Programme Objectives

  • Understand how AI can support Enterprise Risk Management across risk identification, assessment, monitoring, scenario analysis, and reporting.
  • Apply AI-assisted techniques to analyse business processes, risk registers, incidents, controls, external developments, and management information.
  • Use structured prompting for enterprise-risk assessment, risk statements, scenario planning, KRI development, and management reporting.
  • Explore AI-supported approaches for identifying emerging risks, interdependencies, concentration areas, and changes in organisational risk exposure.
  • Build responsible AI-assisted ERM workflows while maintaining governance, confidentiality, professional judgement, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisRisk Register AnalysisScenario AnalysisRisk Reporting AIWorkflow Automation

Who should attend

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

Prerequisites & Participant Readiness

  • Basic understanding of Enterprise Risk Management, business processes, or corporate risk
  • Familiarity with risk registers, controls, incidents, KRIs, or management reports is helpful
  • Basic computer, spreadsheet, and document-handling skills
  • No AI or programming knowledge required
  • No previous AI training required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to Enterprise Risk Management
  • Identifying AI applications across risk identification, assessment, monitoring, scenario analysis, and reporting
  • Understanding AI assistance versus risk-owner and management judgement
  • Recognising limitations such as hallucinations, incomplete evidence, bias, and unsupported conclusions
Practical activities
  • Mapping a typical ERM lifecycle
  • Identifying repetitive and information-intensive ERM activities suitable for AI assistance
  • Comparing a traditional risk-management activity with an AI-assisted approach

Scenarios

Business Strategy to Enterprise Risk Register

Strategic Objective → AI-Assisted Risk Identification → Risk Statements → Risk Categories → Assessment → Controls → Owners → Enterprise Risk Register

Participants use AI to analyse a sample business strategy, identify potential enterprise risks, structure risk statements, and create a preliminary risk register for authorised review.

Enterprise Risk Data to Management Risk Outlook

Risk Register + KRIs + Incidents + External Developments → AI Analysis → Top Risks → Emerging Risks → Interdependencies → Scenario Impacts → Management Report

Participants use AI to combine sample risk information, identify changes in enterprise exposure, assess emerging themes and interdependencies, and prepare a concise management-ready risk outlook.

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