AI strategy and roadmaps
A focused engagement to define what to build first, what to measure, and what to safely defer, grounded in your data reality.
Timeline
2-3 weeks
Format
Workshop plus written roadmap
What you get
- Current-state assessment across data, tooling, and team capability
- A shortlist of AI use cases ranked by value, feasibility, and data readiness
- A sequenced roadmap with explicit dependencies on data and platform work
- Measurement plan: the metrics that define success for each initiative
- Build-versus-buy guidance for the decisions that matter this quarter
Most AI roadmaps fail in one of two directions. They are either wish lists disconnected from the data that would make them possible, or they are so cautious that nothing ships. A useful roadmap sits in the middle: grounded in what your data can support today, honest about what needs building first, and sequenced so early wins fund the harder work.
I run a focused assessment of your data reality, your team’s capability, and your business goals, then write the plan down: what to build first, what to measure, and what to defer without guilt.
Good fit if you are accountable for an AI outcome this year and need a plan your engineers will not quietly route around.