Zachman Framework Alignment Guide
Positioning LocalM™ AiD principles within the Zachman Framework classification schema.
Overview
The Zachman Framework is an enterprise architecture classification schema organized as a 6×6 matrix. Each cell represents the intersection of a perspective (rows) and an interrogative (columns). LocalM™ AiD principles map to specific cells where AI governance artifacts should be classified.
flowchart LR
subgraph zachman["Zachman Framework"]
what["What<br/>(Data)"]
how["How<br/>(Function)"]
where["Where<br/>(Network)"]
who["Who<br/>(People)"]
when["When<br/>(Time)"]
why["Why<br/>(Motivation)"]
end
subgraph localm["LocalM™ AiD Mapping"]
data["GSC: Data<br/>Classification"]
func["DC: Development<br/>Patterns"]
net["TSI: Tool<br/>Integration"]
people["TTA: Training<br/>& Adoption"]
time["DM: Deployment<br/>& Monitoring"]
motiv["PS: Strategy<br/>& Planning"]
end
what --> data
how --> func
where --> net
who --> people
when --> time
why --> motiv
style zachman fill:#1a1a2e,stroke:#4361ee
style localm fill:#1a1a2e,stroke:#00ff94
Zachman Interrogatives Mapping
What (Data)
Zachman Focus: Inventory sets, data entities, classifications
LocalM™ AiD Alignment:
| LocalM™ AiD Principle | Zachman Cell Application |
|---|---|
| GSC-002: Data Classification | Classify data for AI exposure levels |
| GSC-006: Prompt & Context Security | Define context data boundaries |
| DC-003: Context Provision | Specify AI-accessible data sets |
AI Governance Artifacts:
- AI Data Classification Schema
- Context Boundary Definitions
- AI-Accessible Data Inventory
How (Function)
Zachman Focus: Process flows, function hierarchies, workflows
LocalM™ AiD Alignment:
| LocalM™ AiD Principle | Zachman Cell Application |
|---|---|
| DC-001: Human-AI Collaboration | Define AI collaboration workflows |
| DC-002: Iterative Development | Map AI iteration processes |
| DC-004: Code Review & Validation | Specify AI code review procedures |
| TQC-001: AI-Output Testing | Define AI output validation processes |
AI Governance Artifacts:
- AI-Assisted Development Workflow Models
- AI Code Review Process Specifications
- AI Output Validation Procedures
Where (Network)
Zachman Focus: Locations, networks, distributed systems
LocalM™ AiD Alignment:
| LocalM™ AiD Principle | Zachman Cell Application |
|---|---|
| TSI-001: Capability Assessment | Map AI tool deployment locations |
| TSI-002: Tool Integration Standards | Define integration topology |
| TSI-003: Interoperability & Portability | Specify portability requirements |
AI Governance Artifacts:
- AI Tool Deployment Architecture
- AI Integration Network Diagram
- AI Tool Location Matrix
Who (People)
Zachman Focus: Roles, responsibilities, organizations
LocalM™ AiD Alignment:
| LocalM™ AiD Principle | Zachman Cell Application |
|---|---|
| TTA-001: Continuous Learning | Define AI training roles |
| TTA-002: Adoption Governance | Assign adoption responsibilities |
| GSC-003: Access Control | Map AI tool access to roles |
| GSC-001: Governance Framework | Establish governance structure |
AI Governance Artifacts:
- AI Governance RACI Matrix
- AI Tool Access Role Matrix
- AI Training Responsibility Chart
When (Time)
Zachman Focus: Events, cycles, schedules, triggers
LocalM™ AiD Alignment:
| LocalM™ AiD Principle | Zachman Cell Application |
|---|---|
| DM-001: Deployment Controls | Define AI deployment schedules |
| DM-002: Operational Monitoring | Specify monitoring intervals |
| GSC-007: Audit & Accountability | Schedule audit cycles |
AI Governance Artifacts:
- AI Tool Update Schedule
- AI Audit Calendar
- AI Monitoring Event Triggers
Why (Motivation)
Zachman Focus: Goals, strategies, drivers, constraints
LocalM™ AiD Alignment:
| LocalM™ AiD Principle | Zachman Cell Application |
|---|---|
| PS-001: Architecture First | Define AI governance goals |
| PS-002: AI Integration Strategy | Articulate AI adoption drivers |
| PS-003: Capability Maturity Assessment | Set maturity targets |
| PS-004: Risk-Based Adoption | Document risk constraints |
AI Governance Artifacts:
- AI Governance Vision Statement
- AI Adoption Business Drivers
- AI Risk Constraint Matrix
Zachman Perspectives Mapping
Scope (Planner)
Focus: Business context and scope
| Interrogative | AI Governance Content |
|---|---|
| What | AI-applicable data categories |
| How | AI use case scope |
| Where | AI deployment boundaries |
| Who | AI stakeholder groups |
| When | AI adoption horizons |
| Why | AI strategic objectives |
Business Model (Owner)
Focus: Business concepts and models
| Interrogative | AI Governance Content |
|---|---|
| What | AI data classification model |
| How | AI-assisted business processes |
| Where | AI tool business locations |
| Who | AI governance organization |
| When | AI business event triggers |
| Why | AI business goals and strategies |
System Model (Designer)
Focus: Logical system specifications
| Interrogative | AI Governance Content |
|---|---|
| What | AI context data model |
| How | AI workflow specifications |
| Where | AI integration architecture |
| Who | AI access control specifications |
| When | AI event processing rules |
| Why | AI governance rules |
Technology Model (Builder)
Focus: Physical technology specifications
| Interrogative | AI Governance Content |
|---|---|
| What | AI data storage specifications |
| How | AI tool configurations |
| Where | AI network topology |
| Who | AI role-tool assignments |
| When | AI scheduling configurations |
| Why | AI configuration rationale |
Detailed Representations (Subcontractor)
Focus: Implementation details
| Interrogative | AI Governance Content |
|---|---|
| What | AI data implementation details |
| How | AI process implementation |
| Where | AI deployment specifications |
| Who | AI user accounts |
| When | AI timing parameters |
| Why | AI rule implementations |
Functioning Enterprise (User)
Focus: Operational instance
| Interrogative | AI Governance Content |
|---|---|
| What | Live AI data instances |
| How | Running AI workflows |
| Where | Deployed AI tools |
| Who | Active AI users |
| When | AI operational schedule |
| Why | AI operational decisions |
Implementation Matrix
LocalM™ AiD Category to Zachman Cell Mapping
| Category | Primary Column | Secondary Columns |
|---|---|---|
| PS (Planning & Strategy) | Why | When |
| TSI (Tool Selection & Integration) | Where | How |
| TTA (Team Training & Adoption) | Who | How |
| DC (Development & Coding) | How | What |
| TQC (Testing & Quality Control) | How | What, When |
| DM (Deployment & Maintenance) | When | Where |
| GSC (Governance, Security & Compliance) | Who, What | All |
Using This Mapping
Step 1: Identify Current Zachman Artifacts
Review your existing enterprise architecture artifacts and identify which cells are populated.
Step 2: Locate AI Governance Gaps
For each cell, determine whether AI governance content is adequately addressed.
Step 3: Apply LocalM™ AiD Principles
Use the mapping tables above to identify which LocalM™ AiD principles address gaps in each cell.
Step 4: Create AI Governance Artifacts
Develop the artifacts recommended for each cell at the appropriate perspective level.
Step 5: Integrate into Repository
Store AI governance artifacts in your architecture repository, properly classified by Zachman cell.
Next Steps
- Audit your Zachman cells - Identify which cells lack AI governance content
- Prioritize by risk - Focus first on cells where AI governance gaps create business risk
- Map to LocalM™ AiD - Use this guide to select applicable principles
- Create artifacts - Develop AI governance content for priority cells
- Integrate and govern - Add to your architecture repository and governance process