AI Value Sprint
Three weeks inside your operation to find where AI pays, and what to build first.
Why this exists
Most organizations have too many AI ideas and not enough engineered builds. The Value Sprint is the structured way to stop generating slides and start producing the one build worth making first — with a baseline you can be measured against.
of companies are “future-built” for AI — generating substantial value. BCG · 2025
What you get
01
Opportunity map
A ranked view of every candidate use-case — by economic value, feasibility, data readiness and operating risk.
02
Build baseline
Clear pre-state metrics so the next build has something to be measured against. Without a baseline there is no value capture.
03
First build spec
Scope, working assumptions, success criteria and the team shape required to ship it.
How it runs
- Week 1
Frame
Executive interviews · workflow mapping · candidate use-case longlist · economic model.
- Week 2
Diagnose
Feasibility deep-dives · data readiness · constraint check · ranked shortlist.
- Week 3
Decide
Build selection · baseline definition · scope writeup · partner sign-off.
In practice
“Before the Sprint we had eleven AI ideas competing for the same quarter. We finished with one, with numbers, and a team that could ship it.”
When to run this
Yes — when
- →You have multiple AI candidates and no engineered way to choose between them.
- →Leadership wants a measurable starting point, not another deck.
- →You’re committing real budget to AI in the next two quarters.
No — when
- →You’ve already chosen the build and know exactly what it needs.
- →You don’t yet have an executive sponsor for the work.
Then we build.
What comes after the Sprint depends on what it finds — a decision cockpit, an automated workflow, an agent, a data foundation. Often several.