Section 4

Framework Structure

Framework, Methods and Artifacts — what to consider, how to decide, what evidence to produce.

AI4EA consists of three complementary elements:

ElementPurposeExamples
FrameworkDefines what must be consideredSeven layers and four Core Engine pillars
MethodsDefines how important decisions are madeReadiness, UCPS, sourcing assessment, phase gates, continuous evaluation
ArtifactsDefines the evidence decisions should produceVision, portfolio, architectures, operating model, roadmap and value scorecard

In practical terms, AI4EA defines what to consider, how to make architecture decisions, and what evidence those decisions should produce.

1

Strategic Governance & Vision

Align AI with business strategy, enterprise architecture and responsible innovation.

Business Strategy & ObjectivesAI Vision & PrinciplesTarget Operating Model & Value ThemesStakeholder Alignment
2

AI Opportunity & Use Case Portfolio

Identify, assess and prioritize high-value AI use cases.

Use Case DiscoveryValue & Feasibility AssessmentRisk & Compliance ReviewPrioritization & Roadmap
3

AI4EA Readiness Model

Ensure the enterprise is ready to adopt and scale AI.

DataTechnology & PlatformGovernance & RiskPeople & Culture
4

The Core Engine — 4 Pillars

Architect, deliver and govern AI solutions at enterprise scale.

AI Sourcing & Model StrategyData & Knowledge ArchitectureAI Integration & OrchestrationGovernance, Security & Economics
5

Federated Operating Model

Balance central platform capabilities with domain-specific execution.

Central AI HubEmbedded Domain SpokesShared ServicesEnablement
6

Phase-Gated Execution

Start focused, deliver value early, and scale with confidence.

DiscoverDefineBuildDeployScale
7

Enterprise Value & ROI

Measurable outcomes for a more efficient, innovative and resilient enterprise.

Productivity & EfficiencyFaster Time to ValueTrusted Decision-MakingRisk & Compliance Posture
The seven adoption layers