Process
Three phases to AI transformation
How to assess your business's AI readiness, then implement without theater: discover, build, launch. Each phase has activities, an outcome, and a clock.
01
Discover & Strategize
Weeks 1–3
Timeline: 2–3 weeks
Key activities
- • Stakeholder interviews (leadership, operations, IT)
- • Workflow documentation and process mapping
- • Data audit and AI readiness assessment
- • Competitive and industry analysis
- • Opportunity prioritization workshop
Outcome
- • Current state analysis
- • High-impact opportunities, prioritized
- • Technology recommendations
- • Implementation roadmap
- • Budget and resource requirements
- • Risk mitigation plan
02
Plan & Build
Weeks 4–12
Timeline: 4–8 weeks
Key activities
- • Detailed implementation planning
- • Tool selection and licensing
- • System architecture and integration design
- • Data pipeline development
- • Testing and quality assurance
- • Training and change management
Outcome
- • Integrated systems ready for launch
- • Team trained on new tools and processes
- • Documentation and playbooks
- • Rollout plan with contingencies
- • Success metrics defined
03
Launch & Optimize
Weeks 13+
Timeline: Ongoing
Key activities
- • Phased rollout (pilot → full deployment)
- • Real-time support and troubleshooting
- • Performance monitoring and KPI dashboards
- • Process refinement from usage data
- • Ongoing team enablement
- • Quarterly optimization reviews
Outcome
- • Live systems delivering measured results
- • Team confident with the new tools
- • Metrics tracked and optimized
- • Continuous improvement roadmap
- • Long-term strategic partnership