Browse the Body of Knowledge
772 articles organized across 20 knowledge domains, six COMPEL stages, and four depth levels. Browse by any axis below.
By Knowledge Domain
AI Leadership and Sponsorship
Executive champions driving AI transformation with authority and effectiveness
AI Talent and Skills
Depth and breadth of technical AI expertise across the organization
AI Literacy and Culture
Non-technical staff understanding of AI concepts and constructive engagement
Change Management Capability
Capacity to manage behavioral, cultural, and structural transitions
AI Use Case Management
Identifying, prioritizing, validating, and tracking AI opportunities
Data Management and Quality
Data governance, quality assurance, cataloging, and accessibility practices
ML Operations and Deployment
MLOps practices including model versioning, testing, deployment, and monitoring
AI Project Delivery
Methodology and discipline applied to AI project execution
Continuous Improvement Processes
Mechanisms for capturing lessons and systematically improving AI delivery
Data Infrastructure
Data storage, pipelines, integration, and platform architecture maturity
AI/ML Platform and Tooling
Availability and adoption of model development, training, and deployment platforms
Integration Architecture
Ability to integrate AI capabilities into enterprise systems and workflows
Security and Infrastructure
Security posture specific to AI workloads and infrastructure hardening
AI Strategy and Alignment
Clarity and organizational adoption of AI strategy connected to business objectives
AI Ethics and Responsible AI
Policies, review processes, and commitment to ethical AI development
Regulatory Compliance
Readiness to comply with current and emerging AI-specific regulations
Risk Management
Frameworks for identifying, assessing, and mitigating AI-specific risks
AI Governance Structure
Organizational bodies, decision rights, and accountability mechanisms
AI Environmental Sustainability
Monitoring, measuring, and minimizing the environmental footprint of AI systems including energy consumption, carbon emissions, and resource usage
AI Supply Chain and Third-Party Governance
Governance of AI systems procured from, provided by, or dependent on external parties — including vendor due diligence, shadow AI discovery, AI bill of materials, and contractual governance