Framework Specification · Version 1.0
AI4EA Specification
AI4EA is organized as a concise practitioner specification. It defines the framework structure, decision methods and minimum architecture artifacts required to move from AI ambition to governed enterprise capability. Align. Architect. Govern. Scale. Measure.
Download the PDF specification1–2Overview, Purpose & ScopeWhy AI4EA exists, the five questions it answers, what it covers and who it is written for.3Guiding PrinciplesThe ten principles that govern how AI4EA is applied.4Framework StructureFramework, Methods and Artifacts — what to consider, how to decide, what evidence to produce.5Strategic Vision & Business AlignmentEstablishing the enterprise context so AI investment supports explicit strategic priorities.6AI Opportunity & Use Case PortfolioDiscover, assess, review, prioritize and roadmap AI opportunities as an enterprise portfolio.7AI4EA Readiness ModelAssess Data, Technology & Platform, Governance & Risk and People & Culture across five levels.8AI4EA Core EngineFour interconnected architecture pillars: sourcing, knowledge, integration and governance.9Federated Operating ModelA Central AI Hub for consistency, embedded domain spokes for relevance and ownership.10Phase-Gated Execution ModelFive phases and four gates that move an initiative from discovery to sustainable scale.11Enterprise Value & ROISeparating technical performance from enterprise outcomes, and measuring across three scopes.12Continuous Evaluation & ImprovementMeasure → Evaluate → Govern → Improve → Re-architect, as a permanent capability.13Artifacts & DeliverablesThe minimum sufficient architecture evidence each layer should produce.14Enterprise AI Reference ArchitectureAn illustrative layered mapping from consumption to infrastructure, with cross-cutting concerns.15Applying AI4EAEight steps for adopting the framework proportionately.16–17Conformance, Tailoring & Closing PerspectiveConformance is decision coverage, not technology selection.