Role-Based Programme
RB1695

AI-Powered Cybersecurity Risk Management

Intelligent Threat Analysis, Control Assurance & Cyber 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 cybersecurity risk identification, assessment, control review, monitoring, incident analysis, and governance.
  • Use AI to analyse security policies, risk registers, vulnerability information, control evidence, incident records, audit findings, and threat intelligence.
  • Build repeatable AI-assisted workflows for cyber risk assessment, security-control reviews, evidence analysis, issue tracking, and management reporting.
  • Apply AI to identify recurring security themes, control gaps, emerging cyber risks, remediation priorities, and areas requiring specialist investigation.
  • Design responsible AI-enabled cybersecurity risk workflows with appropriate controls for confidentiality, sensitive security information, accuracy, auditability, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisCyber Risk AnalyticsSecurity Control AssessmentVulnerability & Incident IntelligenceThreat Intelligence AnalysisReporting & Dashboard ToolsWorkflow Automation

Who should attend

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

Prerequisites & Participant Readiness

  • Working knowledge of cybersecurity, information security, IT risk, audit, or technology controls
  • Familiarity with security policies, cyber risks, control frameworks, incidents, vulnerabilities, or assurance activities
  • 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, automation, and their relevance to cyber risk management
  • Mapping AI opportunities across cybersecurity governance, risk, controls, monitoring, and assurance
  • Understanding AI assistance versus cybersecurity specialist and risk-owner judgement
  • Recognising confidentiality, hallucination, model-risk, and sensitive-security-data concerns
Practical activities
  • Mapping a Cybersecurity Risk lifecycle and identifying appropriate AI use cases
  • Comparing manual and AI-assisted cyber risk activities
  • Creating an AI opportunity matrix based on value, sensitivity, and risk

Scenarios

Technology Environment to Cyber Risk Assessment

Business / Technology Context → Asset Identification → Threat & Vulnerability Analysis → Control Mapping → Risk Scoring → Gaps → Remediation Priorities → Executive Risk Brief

Participants use AI-assisted methods to analyse a simulated technology environment, identify cyber risks, map existing controls, prioritise gaps, and prepare a structured management-ready cybersecurity risk assessment.

Cyber Findings to Continuous Risk Monitoring Workflow

Vulnerabilities + Access Exceptions + Incidents + Audit Findings + Remediation Data → AI Analysis → Priority Risks → Trends → Automated Follow-Up → Dashboard → Management Reporting

Participants design an AI-enabled cyber-risk monitoring workflow that consolidates multiple risk signals, highlights overdue and recurring issues, improves remediation visibility, and supports executive reporting while retaining all security-critical decisions with authorised professionals.

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