Implementation Guide
Use this after you have finished the Foundation and Playbook reading pass.
Work the six steps in order. Each step includes what happens, who is involved, concrete actions, and the evidence you should produce.
End-to-End Map
| Step | Focus | Primary Output |
|---|---|---|
| 1. Value (Why) | Define why AI matters now | Value charter and KPI baseline |
| 2. Use Cases (Where) | Select where AI creates value first | Ranked use case portfolio |
| 3. Operating Model (How) | Define how humans and AI collaborate | Future-state workflow and accountability |
| 4. Foundation (What Enables It) | Build data and technology baseline | Deployable technical foundation |
| 5. Governance (Control and Trust) | Apply risk, privacy, and compliance controls | Policy, controls, and monitoring |
| 6. Execution (How It Happens) | Deliver, adopt, and scale | Live solutions with ownership |
1. Value (Why)
Define why AI matters now and lock outcome targets before selecting use cases. Clear value definition prevents technology-first projects with unclear business outcomes.
What Happens
- Define value dimensions: efficiency, quality, capability
- Set target outcomes and decision deadlines
- Align sponsors and funding owners
Who Is Involved
- Executive leadership
- Strategy and planning
- Finance and business control
Actions
- Define value dimensions (efficiency, quality, capability).
- Capture current baseline and target values.
- Assign benefits owner and review cadence.
Evidence
- Value statement
- KPI baseline and target table
- 30/90/180-day benefits review plan
Output
Value statement, KPI baseline, and success criteria.
2. Use Cases (Where)
Select where AI creates value first by scoring a ranked portfolio. A scored portfolio creates a repeatable way to identify and prioritize opportunities.
What Happens
- Build candidate list from pain points and opportunities
- Classify by type: automation, augmentation, generation, prediction, optimization
- Score by impact, effort, risk, and readiness
Who Is Involved
- Business owners
- Operations and product teams
- AI and technology leads
Actions
- Create use case inventory.
- Classify each use case type.
- Score by impact, effort, feasibility, and risk.
- Select top candidates for delivery.
Evidence
- Use case portfolio with owners
- Prioritization rubric
- Delivery wave plan
Output
Ranked use case portfolio with ownership.
3. Operating Model (How)
Define how humans and AI collaborate, including handoffs and override authority. An explicit operating model clarifies accountability and when humans must intervene.
What Happens
- Select interaction mode (assistive, co-pilot, autonomous)
- Redesign workflows and define handoff points
- Establish exception routing and override authority
Who Is Involved
- Process owners
- Department leads
- Solution architects
- End users
Actions
- Choose operating mode (assistive, co-pilot, autonomous).
- Define decision boundaries and escalation routes.
- Map handoffs and exception queues.
Evidence
- Workflow map
- RACI matrix
- Exception and override policy
Output
Approved workflow design and role accountability.
4. Foundation (What Enables It)
Build the data and technology baseline required for reliable delivery. Data and platform readiness determine AI quality and reliability.
What Happens
- Validate data readiness, quality, and permissions
- Select approved tools and model patterns
- Implement integration, identity, and observability
Who Is Involved
- Data engineering
- IT and platform teams
- Security and architecture
Actions
- Validate data quality, lineage, and permissions.
- Select approved model and tool stack.
- Implement integration, identity, and observability.
- Define release and rollback process.
Evidence
- Data readiness report
- Architecture decision record
- Integration and monitoring checklist
Output
Minimum viable foundation ready for deployment.
5. Governance (Control and Trust)
Apply risk, privacy, and compliance controls before scale. Governance reduces legal, security, and reputational risk.
What Happens
- Define policy guardrails for allowed and restricted use
- Apply privacy, security, and compliance controls
- Set model and output risk checks and monitoring
Who Is Involved
- Security and compliance
- Legal and risk
- IT governance
- Leadership (risk tolerance decisions)
Actions
- Define risk tiers for AI use cases.
- Apply controls for privacy, security, and compliance.
- Measure bias, accuracy, drift, and output quality.
- Enforce auditability and human override.
Evidence
- AI governance policy
- Risk register
- Monitoring dashboard and alert thresholds
Output
Governed deployment package and monitoring plan.
6. Execution (How It Happens)
Deliver, adopt, and scale in short cycles with clear ownership. Execution converts plans into measurable business outcomes.
What Happens
- Assign delivery roles: Explorer, Operator, Architect, Orchestrator
- Build, test, deploy, and stabilize in short cycles
- Train users and drive adoption with feedback loops
Who Is Involved
- Delivery and platform teams
- Business users and team leads
- Change management
Actions
- Select delivery approach (predictive, adaptive, or hybrid).
- Assign core roles and responsibilities.
- Run build-test-deploy cycles with adoption support.
- Iterate using measurement feedback.
Evidence
- 6-12 month roadmap
- Role assignment table
- Adoption and improvement plan
Output
Live AI-enabled operations with clear ownership.
Measurement Loop
Measure and decide continuously across every step.
| Dimension | Example Metrics |
|---|---|
| Efficiency | Cycle time, cost per transaction, throughput |
| Quality | Error rate, rework rate, consistency |
| Capability | New outputs, decision speed, adoption rate |
Decision Options
- Improve and iterate
- Scale and expand
- Stop or retire
Alignment Summary
| Framework | Where It Helps Most |
|---|---|
| ITIL | Service design, transition, and continual improvement |
| PMBOK | Portfolio prioritization and benefits realization |
| NIST AI RMF | AI risk governance lifecycle |
| COBIT | Governance structures and accountability |
When you need printable worksheets or readiness scoring, use the Reference section alongside these steps.