v0.0.1 • In Peer Review

TOGAF Alignment Guide

Mapping LocalM™ AiD Enterprise Architecture Principles to TOGAF ADM and architecture domains.

FRAMEWORK TOGAF 10 / ADM
AUDIENCE Enterprise Architects
ALIGNMENT Full Mapping
STATUS ✅ Available

Overview

TOGAF (The Open Group Architecture Framework) provides a comprehensive approach to enterprise architecture through the Architecture Development Method (ADM). LocalM™ AiD principles extend TOGAF to address AI-assisted development governance—a domain that didn’t exist when TOGAF was originally developed.

flowchart TB
    subgraph togaf["TOGAF ADM"]
        prelim["Preliminary"]
        a["A: Vision"]
        b["B: Business"]
        c["C: Information"]
        d["D: Technology"]
        e["E: Opportunities"]
        f["F: Migration"]
        g["G: Implementation"]
        h["H: Change Mgmt"]
        req["Requirements"]
    end

    subgraph localm["LocalM™ AiD Integration Points"]
        ps["PS: Planning & Strategy"]
        tsi["TSI: Tool Selection"]
        gsc["GSC: Governance"]
    end

    prelim --> ps
    a --> ps
    d --> tsi
    g --> gsc
    h --> gsc

    style togaf fill:#1a1a2e,stroke:#4361ee
    style localm fill:#1a1a2e,stroke:#00ff94

ADM Phase Alignment

Phase A: Architecture Vision

TOGAF Focus: Establishing architecture vision and stakeholder engagement

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
PS-001: Architecture First Include AI tool governance in architecture vision
PS-002: AI Integration Strategy Define AI adoption strategy as part of vision
PS-003: Capability Maturity Assessment Assess current AI governance maturity

Key Artifacts:

  • AI Governance Vision Statement
  • AI Tool Capability Requirements
  • Stakeholder AI Concerns Matrix

Phase B: Business Architecture

TOGAF Focus: Developing business architecture to support architecture vision

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
PS-004: Risk-Based Adoption Map AI risks to business processes
TTA-001: Continuous Learning Define AI training in capability model

Key Artifacts:

  • AI-Augmented Process Models
  • AI Skills Capability Map
  • AI Risk Business Impact Assessment

Phase C: Information Systems Architecture

TOGAF Focus: Data and application architecture development

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
DC-003: Context Provision Define AI context data requirements
GSC-002: Data Classification Classify data for AI exposure
GSC-006: Prompt & Context Security Secure AI data interfaces

Key Artifacts:

  • AI Data Classification Schema
  • AI-Accessible Data Catalog
  • Context Security Architecture

Phase D: Technology Architecture

TOGAF Focus: Technology infrastructure to support applications

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
TSI-001: Capability Assessment Evaluate AI tools against requirements
TSI-002: Tool Integration Standards Define AI tool integration patterns
TSI-003: Interoperability & Portability Ensure AI tool independence

Key Artifacts:

  • AI Tool Technology Reference Model
  • AI Integration Standards Document
  • AI Tool Selection Criteria

Phase E: Opportunities and Solutions

TOGAF Focus: Identifying transformation opportunities

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
DC-001: Human-AI Collaboration Define AI collaboration patterns
DC-002: Iterative Development Plan incremental AI adoption

Key Artifacts:

  • AI Adoption Roadmap
  • AI Capability Gap Analysis
  • AI Transformation Work Packages

Phase F: Migration Planning

TOGAF Focus: Prioritizing and planning migration

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
PS-003: Capability Maturity Assessment Define maturity-based migration
TTA-002: Adoption Governance Plan controlled rollout

Key Artifacts:

  • AI Governance Maturity Roadmap
  • AI Tool Migration Plan
  • AI Training Deployment Schedule

Phase G: Implementation Governance

TOGAF Focus: Providing architectural oversight of implementation

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
GSC-001: Governance Framework Establish AI governance board
GSC-003: Access Control Implement AI tool access controls
GSC-007: Audit & Accountability Deploy AI audit mechanisms

Key Artifacts:

  • AI Governance Board Charter
  • AI Tool Access Control Matrix
  • AI Audit Trail Requirements

Phase H: Architecture Change Management

TOGAF Focus: Managing changes to architecture

LocalM™ AiD Alignment:

LocalM™ AiD Principle TOGAF Integration
DM-001: Deployment Controls Manage AI in deployment pipeline
DM-002: Operational Monitoring Monitor AI operations

Key Artifacts:

  • AI Configuration Change Process
  • AI Tool Update Procedures
  • AI Operational Dashboard Requirements

TOGAF Architecture Domains

Business Architecture

  • LocalM™ AiD Categories: PS (Planning & Strategy), TTA (Team Training & Adoption)
  • Focus: AI adoption strategy, organizational readiness, skills development

Data Architecture

  • LocalM™ AiD Categories: GSC (Governance, Security & Compliance)
  • Focus: Data classification for AI, context security, audit trails

Application Architecture

  • LocalM™ AiD Categories: DC (Development & Coding), TQC (Testing & Quality Control)
  • Focus: AI-assisted development patterns, AI-generated code quality

Technology Architecture

  • LocalM™ AiD Categories: TSI (Tool Selection & Integration), DM (Deployment & Maintenance)
  • Focus: AI tool selection, integration, deployment, and operations

Implementation Approach

Stage 1: Foundation

TOGAF Activities:

  • Establish AI governance as Architecture Principle
  • Add AI tools to Technology Reference Model
  • Include AI governance in Architecture Vision template

LocalM™ AiD Principles: PS-001, PS-002, GSC-001

Stage 2: Integration

TOGAF Activities:

  • Map AI principles to ADM deliverables
  • Train architecture team on AI governance
  • Add AI review gates to Architecture Compliance process

LocalM™ AiD Principles: TSI-001, TSI-002, TTA-001

Stage 3: Optimization

TOGAF Activities:

  • Automate AI governance compliance checks
  • Integrate AI audit trails with Architecture Repository
  • Establish AI governance metrics in Architecture Performance

LocalM™ AiD Principles: GSC-007, DM-002, All maturity Level 3

TOGAF Artifacts Extended for AI

TOGAF Artifact AI Governance Extension
Architecture Principles Add LocalM™ AiD principles as supplementary principles
Technology Reference Model Include AI tools category
Architecture Contract Add AI governance compliance clauses
Implementation Governance Model Include AI-specific review gates
Architecture Repository Store AI governance artifacts

Next Steps

  1. Map your ADM - Identify where you are in current architecture cycles
  2. Assess gaps - Determine which LocalM™ AiD principles address unmet AI governance needs
  3. Extend artifacts - Add AI governance content to existing TOGAF deliverables
  4. Train architects - Ensure architecture team understands AI governance principles
  5. Establish governance - Add AI review gates to your Architecture Compliance process