← AI Strategy & Implementation
Overview
AI strategy isn’t a slide with ChatGPT on the cover - it’s deciding where probabilistic tools earn their place alongside deterministic software and human judgment. We help you prioritise use cases by value, feasibility, data sensitivity, and operational readiness - then sequence work so pilots prove something before you scale spend.
Where this helps
- Executives asked “what’s our AI strategy?” without a clear answer
- Innovation leaders stuck between vendor hype and risk/compliance caution
- Functional heads (support, ops, marketing) with concrete friction points worth testing
What we focus on
- Opportunity mapping - Jobs-to-be-done, failure modes, human-in-loop expectations
- Data & privacy - Classification, retention, training boundaries, vendor posture
- Economic model - Token/API costs, support burden, and value hypotheses
- Roadmap - Phases, owners, success metrics, kill criteria
How we work
Deliverables read like engineering and finance can act on them - not vague transformation poetry. Strategy hands naturally into implementation and governance when you’re ready to ship.