v0.0.1 • In Peer Review

Zachman Framework Alignment Guide

Positioning LocalM™ AiD principles within the Zachman Framework classification schema.

FRAMEWORK Zachman Framework 3.0
AUDIENCE Enterprise Architects
ALIGNMENT Cell Mapping
STATUS ✅ Available

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

  1. Audit your Zachman cells - Identify which cells lack AI governance content
  2. Prioritize by risk - Focus first on cells where AI governance gaps create business risk
  3. Map to LocalM™ AiD - Use this guide to select applicable principles
  4. Create artifacts - Develop AI governance content for priority cells
  5. Integrate and govern - Add to your architecture repository and governance process