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Enterprise AI Governance Playbook

License: MIT Last Commit

An end-to-end operating playbook for enterprise AI — from intake and prioritisation through release, monitoring, and continuous improvement.


Why this exists

Many organisations experiment with AI without a disciplined operating model. Projects are approved without clear criteria, released without structured gates, and abandoned without retrospectives.

This playbook connects the full lifecycle into a coherent operating system — embedding Lean Six Sigma discipline into AI governance.


Playbook lifecycle

flowchart LR
    A[Intake] --> B[Prioritisation]
    B --> C[Delivery governance]
    C --> D[Release readiness]
    D --> E[Post-release monitoring]
    E --> F[Improvement loops]
    F --> A
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What's included

Playbook phases

Phase Document
Intake playbook/intake.md
Prioritisation playbook/prioritization.md
Release playbook/release.md
Monitoring playbook/monitoring.md
Improvement playbook/improvement.md

Lean Six Sigma integration

Topic Document
AI operating model lean-six-sigma/ai-operating-model.md
Metrics and CTQs lean-six-sigma/metrics-and-ctqs.md

Templates

Template Use for
templates/intake-form.md Capturing AI project requests
templates/prioritization-matrix.csv Scoring and ranking initiatives
templates/improvement-review.md Post-release retrospectives

Companion repositories


Related repositories

This repository is part of a connected toolkit for responsible AI operations:

Repository Purpose
Enterprise AI Governance Playbook End-to-end AI operating model from intake to improvement
AI Release Governance Framework Risk-based release gates for AI systems
AI Release Readiness Checklist Risk-tiered pre-release checklists with CLI tool
AI Accountability Design Patterns Patterns for human oversight and escalation
Multi-Agent Governance Framework Roles, authority, and escalation for agent systems
Multi-Agent Orchestration Patterns Sequential, parallel, and feedback-loop patterns
AI Agent Evaluation Framework System-level evaluation across 5 dimensions
Agent System Simulator Runnable multi-agent simulator with governance controls
LLM-powered Lean Six Sigma AI copilot for structured process improvement

Shared in a personal capacity. Open to collaborations and feedback — connect on LinkedIn or Medium.

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An end-to-end playbook for enterprise AI governance covering intake, prioritization, release, monitoring, and continuous improvement.

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