AI Use Case Selection & Prioritization
Pick the right pilots. Prove value fast.
Most companies have a long list of AI ideas and no way to tell which ones are worth funding. Pilots launch without agreed success measures, so results are open to debate — and stalled proofs-of-concept just sit there, draining budget and confidence.
If you're a product or innovation leader, an executive sponsoring AI pilots, or a programme team trying to unstick a proof-of-concept that's gone quiet, this is built for you.
What we help you do
We turn a long list of ideas into a short list you can defend to the board.
01
Separate the promising from the popular
Every idea assessed the same way, on business value and practical feasibility.
02
Design pilots that actually prove something
Clear success measures agreed up front, so results are not open to interpretation.
03
Decide honestly what to scale
Defined gates for scaling, changing direction, or stopping without blame.
What's included
A disciplined path from long list to validated decision.
- Use-case long list, triage and shortlisting
- Business-case framing and feasibility assessment
- Proof-of-concept design with defined success measures
- Scale, pivot or stop evaluation criteria
How it works
- 01
Collect
Gather every candidate use case already circulating in the business.
- 02
Score
Assess each one for value, feasibility, data readiness and risk.
- 03
Design
Build a proof-of-concept plan for the shortlist, with measures agreed in advance.
- 04
Decide
Review results against those measures and recommend what scales.
What you get
A clear, defensible portfolio of what to build next.
- Use-case canvas and prioritised shortlist
- Proof-of-concept plan and measurement framework
- Validation report with a scaling recommendation
Who it's for
- Product and innovation leaders picking what to pilot next
- Executives sponsoring AI pilots who need to explain the spend
- Programme teams trying to unstick a proof-of-concept that's gone quiet