Transfer Ownership
The goal is independence, not dependency.
What Happens in This Phase
- Governance frameworks: decision trees, escalation paths, approval workflows, and accountability structures for AI systems
- Operational runbooks: step-by-step guides for system management, incident response, and routine maintenance
- Model monitoring playbooks: drift detection, retraining triggers, performance thresholds, and alerting configurations
- Hands-on team training through paired implementation — not classroom lectures, not slide-based workshops
- Documentation that teams actually use: concise, task-oriented guides with decision frameworks, not comprehensive reference manuals
What Gets Delivered
Internal Capability
Teams equipped to operate, maintain, and evolve AI systems independently. No ongoing consulting dependency required.
Governance That Scales
Governance structures designed to grow with the organization — not static policies that become obsolete within a quarter.
Decision Confidence
Leadership and engineering teams confident enough to make AI investment and deployment decisions without external validation.
Foundation for Next Phase
A clear foundation for the next wave of AI investment — built on lessons learned and operational maturity, not starting from scratch.
AI Governance Framework Starter Kit
A template for building internal AI governance policies covering ethics, risk management, model oversight, and decision authority.
Ready to Build Lasting AI Capability?
The best consulting engagements end with the client not needing the consultant. That is the goal from day one.