Artificial Intelligence
Purpose of the Meta-domain
To establish Artificial Intelligence as a cross-cutting capability that strengthens all the domains of the model, enabling augmented decisions, intelligent automation, continuous learning, and execution at scale, without becoming a technology “silo”.
What Does It Govern / What Does It Design?
- AI usage strategy aligned with organizational objectives
- AI lifecycle (design, evaluation, operation, and continuous improvement)
- AI architectures: analytics, ML, GenAI, RAG, and agents
- Organizational knowledge management for AI (context, semantics, trusted sources)
- Quality and control of results (evaluation, monitoring, improvement)
- Responsible AI principles: traceability, transparency, control, human-in-the-loop
Value and Advantages for the Organization
- Faster, better-informed decisions
- Operational efficiency at scale through intelligent automation
- Accelerated organizational learning (reusable knowledge)
- Greater responsiveness to changes and events
- Measurable productivity gains without proportional growth in structure
Risks of Not Managing It Properly
- “Shadow AI”: isolated initiatives without control or coherence
- Inconsistent or unreliable results due to lack of context and semantics
- Privacy, compliance, and data-leakage risks
- Dependence on vendors or tools without an architectural strategy
- Agents and automations making decisions without boundaries or traceability
Dependencies and Relationships with Other Domains
- Business Defines objectives, use cases, boundaries, and success criteria
- Applications Expose capabilities and systems that AI and agents consume
- Agents Consume AI to execute tasks and decisions autonomously and in a governed way
- Integration Connects sources, services, and events to feed AI and automation
- Data Provides canonical models and semantics so that GenAI “understands” the business
- Security Controls privacy, permissions, auditing, and responsible use of AI
- Platform Enables compute, managed services, and AI scalability
Key message: AI is not just another component. It is the “intelligence engine” that connects and optimizes the entire architecture. AI without architecture generates costs and risks. AI with architecture generates value, control, and scale.