Reading Path
CISO
AI risk, security, shadow AI discovery, and safe autonomy for agentic systems.
What Are the Primary Concerns for the CISO?
- → Shadow AI discovery and classification
- → Agent safety and tool controls
- → Data protection and residency
- → Threat modeling for AI systems
- → Incident response for AI failures
Which COMPEL Domains Are Relevant to the CISO?
- Risk Management & AI EthicsRisk identification, assessment, mitigation, ethics operationalized, bias and fairness, responsible AI, risk appetite.
- Agent Governance & AutonomyAgentic AI architecture, autonomy classification, agent safety, tool access controls, multi-agent orchestration, HITL design.
- AI Governance & ComplianceGovernance frameworks, regulatory landscape, audit preparedness, compliance operations, ISO 42001, policy lifecycle.
- Data Governance & ReadinessData quality, data architecture, data management, data readiness assessment, data infrastructure.
What Articles Are Recommended for the CISO? (78)
- M1.2Stage Gate Decision Framework
- M1.2The COMPEL Cycle: Iteration and Continuous Improvement
- M1.2Mapping COMPEL to Your Organization
- M1.2Integration with Existing Frameworks
- M1.2Evaluating Agentic AI: Goal Achievement and Behavioral Assessment
- M1.2Agent Learning, Memory, and Adaptation: Governance Implications
- M1.2Transformation Enablers
- M1.2Mandatory Artifacts and Evidence Management Across the COMPEL Cycle
- M1.2The COMPEL Operating Model: Roles, RACI, and Decision Rights
- M1.2Entry and Exit Criteria: Stage Gate Readiness Across the COMPEL Cycle
- M1.4Agentic AI Architecture Patterns and the Autonomy Spectrum
- M1.4Tool Use and Function Calling in Autonomous AI Systems
- M1.5The AI Governance Imperative
- M1.5The Global AI Regulatory Landscape
- M1.5Building an AI Governance Framework
- M1.5AI Risk Identification and Classification
- M1.5AI Risk Assessment and Mitigation
- M1.5AI Ethics Operationalized
- M1.5Data Governance for AI
- M1.5Model Governance and Lifecycle Management
- M1.5Audit Preparedness and Compliance Operations
- M1.5Governance Maturity and the Path Forward
- M1.5Grounding, Retrieval, and Factual Integrity for AI Agents
- M1.5Safety Boundaries and Containment for Autonomous AI
- M2.2Agentic AI Maturity Assessment: Extending the 18-Domain Model
- M2.4Human-Agent Collaboration Patterns and Oversight Design
- M2.4Operational Resilience for Agentic AI: Failure Modes and Recovery
- M2.5Designing Measurement Frameworks for Agentic AI Systems
- M2.5Audit Trails and Decision Provenance in Multi-Agent Systems
- M2.5Agentic AI Cost Modeling: Token Economics, Compute Budgets, and ROI
- M3.3Enterprise Agentic AI Platform Strategy and Multi-Agent Orchestration
- M3.4Governance as Strategic Advantage
- M3.4Multinational Governance Architecture
- M3.4Proactive Regulatory Engagement
- M3.4Advanced Ethics Architecture
- M3.4AI Risk Governance at Enterprise Scale
- M3.4Third-Party and Supply Chain AI Governance
- M3.4Intellectual Property Strategy for AI
- M3.4Audit and Assurance for Enterprise AI
- M3.4Governance Evolution and Maturity
- M3.4The AITGP as Governance Architect
- M3.4Agentic AI Governance Architecture: Delegation, Authority, and Accountability
- M3.4Agentic AI Risk Taxonomy and Enterprise Risk Framework Extension
- M3.4Measuring AI Responsibility: Bias, Fairness, and Explainability Metrics
- M3.6The Capstone Challenge — Integrating the Full COMPEL Body of Knowledge
- M3.6Selecting and Scoping the Capstone Organization
- M3.6The Enterprise Transformation Architecture Framework
- M3.6Conducting the Enterprise Assessment
- M3.6Designing the Strategic Transformation Roadmap
- M3.6The Organizational Transformation Design
- M3.6The Technology and Governance Architecture
- M3.6The Measurement and Value Realization Framework
- M3.6Preparing and Delivering the Oral Defense
- M3.6The AITGP Professional — Completing the Journey
- M3.6Measuring AI Reliability: SLOs, Drift, and Incident MTTR
- M4.3Cross-Organizational Governance Architecture Design
- M4.3ISO 42001 Alignment and AI Management System Certification
- M4.3NIST AI RMF Implementation at Enterprise Scale
- M4.3Multi-Jurisdictional Regulatory Harmonization
- M4.3Joint Venture and Consortium AI Governance Models
- M4.3Supply Chain and Ecosystem AI Policy Orchestration
- M4.3Public-Private Partnership Governance for AI Initiatives
- M4.3Enterprise Policy Lifecycle Management and Version Control
- M4.3Cross-Border Data Governance and Sovereignty Architecture
- M4.3The AITP Lead as Governance Harmonization Authority
- M4.3Cross-Organizational Agentic AI Governance and Policy Frameworks
- M4.3Measuring AI Compliance: Control Coverage, Conformity Gaps, and Audit Readiness
- M4.5Industry Standards for Agentic AI: ISO, NIST, and Emerging Frameworks
- M4.6The AITP Lead Capstone — Portfolio Defense Overview
- M4.6Selecting the Multi-Organization Portfolio Scope
- M4.6Portfolio Strategy Document Architecture and Requirements
- M4.6Demonstrating Framework Interoperability in the Portfolio
- M4.6The Governance Harmonization Artifact
- M4.6The Operating Model Blueprint Artifact
- M4.6Portfolio Value Narrative and Executive Impact Case
- M4.6Preparing the Live Panel Defense
- M4.6Scoring Rubric and Evaluation Criteria
- M4.6The AITP Lead — Professional Mastery, Responsibility, and the Path Ahead
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