Consulting Toolkit
AI Implementation Playbooks
Practical frameworks, checklists, and templates for every stage of the AI project lifecycle. Click any playbook to see the full checklist.
Phase 1: Assess
Evaluate your organization's AI readiness and identify opportunities.
Phase 2: Pilot
Run a contained proof-of-concept to validate and learn.
Phase 3: Scale
Expand from pilot to production with governance and change management.
Phase 4: Govern
Establish ongoing oversight, compliance, and continuous improvement.
Phase 1: Assess
AI Readiness Assessment
Score your org's data maturity, talent, and infrastructure.
Use Case Prioritization Matrix
Rank AI opportunities by impact vs. feasibility.
Stakeholder Alignment Workshop
Templates for getting leadership buy-in.
Phase 2: Pilot
Pilot Project Charter Template
Define scope, success metrics, and risk controls.
Vendor Evaluation Scorecard
Compare AI vendors across 15 dimensions.
AI Ethics Checklist
Ensure fairness, transparency, and accountability.
Phase 3: Scale
MLOps Maturity Roadmap
From manual deployments to automated ML pipelines.
Change Management Playbook
Drive adoption with training and communication plans.
AI ROI Measurement Framework
Track and report business value of AI investments.
Phase 4: Govern
AI Governance Framework
Policies, accountability structures, and review processes.
Model Risk Management Policy
Monitor, audit, and manage deployed AI systems.
AI Incident Response Playbook
Handle AI failures, bias incidents, and compliance breaches.