Enterprise Architecture Alignment ensures that AI systems are integrated with your organisation’s broader technical and governance frameworks rather than existing as isolated islands. This includes integration with identity and access management (IAM) systems, alignment with data governance frameworks, adherence to security standards and patterns, compatibility with existing application portfolios, and consistency with architectural principles and technology roadmaps. It means treating AI as part of the enterprise technology ecosystem, not as an exception that bypasses established standards.
Siloed AI implementations create technical debt, security gaps, integration challenges, and duplicated effort. They make it difficult to enforce consistent policies, share data appropriately, or maintain systems over time. This dimension evaluates alignment with enterprise standards.
Why It Matters
Siloed AI systems create technical debt, security gaps, and integration challenges.
Maturity Levels
| Basic | Standard | Advanced | Leading |
|---|---|---|---|
| AI systems are siloed, with no integration into enterprise architecture. | Basic integration with existing systems. | AI aligned with IAM, governance, and security frameworks. | AI embedded in strategic enterprise architecture roadmap. |
📥 Related Resources & Templates
Downloadable templates, examples, and frameworks to help you implement this dimension.
AI Integration Blueprints
PremiumTechnical blueprints for integrating AI systems with enterprise architecture, including API patterns and data flows.