AI USE CASE DISCOVERY AND VALIDATION
AI use-case discovery and validation
We help you discover and validate AI use cases against business value, data readiness and delivery effort, so investment goes to the strongest opportunities.
- A value against feasibility filter that retires fantasies fast
- A weighted scoring matrix, so ranking is defensible not political
- A ranked, owned backlog with baselines captured to prove ROI
Two axes retire the fantasies before analysis begins.
Before scoring anything, we place every candidate on the axes that matter most: how much value it moves, and how feasible it actually is to build and run. A GenAI pilot stalls before production when the value, data access or operating controls are unclear. This quadrant makes those conditions explicit before more delivery is funded.
Prioritise now
Fund these first. The value is high and the build is achievable. The core of the fundable backlog.
Strategic bets
Real payoff, real risk. Stage and de-risk before committing budget. Sequenced behind the quick wins that fund them.
Quick wins
Cheap to prove. Use them to build momentum and credibility. Evidence that the platform works, at low cost.
Avoid
Hard to build, little return. Retire it before it consumes delivery capacity. Retired early, with the reason documented.
The quadrant sorts. The matrix ranks.
We score each surviving candidate across five weighted dimensions, so prioritisation is defensible rather than political.
Weighting is set with your leadership, so a use case cannot score well by being merely interesting. The output is a ranked backlog with estimated value, effort, data dependencies, and a named production owner for each item.
A long list is easy. A fundable few, with owners and baselines, is the hard part we own.
Five steps from a hundred ideas to a fundable few.
Discover
Workshops and interviews across functions to surface candidates, plus a scan for high-value cases the business has not articulated yet.
Filter
Plot every candidate on the value against feasibility quadrant and retire the unviable ones before they consume analysis.
Score
Rate survivors across the five weighted dimensions to produce a defensible ranking.
Validate
Data checks and a lightweight proof on the top candidates, with a baseline metric captured so ROI can later be proven.
Package
A ranked, owned backlog that flows straight into roadmap and build.
Time-boxed, so you reach decisions in weeks, not quarters.
Fund a use case with evidence behind it.
Problem clarity. Define the decision or workflow to improve, who owns it and how it is measured today.
Feasibility evidence. Test the important assumptions about data, integration and user acceptance.
A funding recommendation. Document expected value, costs and risks, with a clear proceed, revise or stop decision.
Discovery sits between a baseline and a roadmap.
Maturity Assessment
Discovery works best on a known baseline, so start with an honest maturity score.
Roadmap and Blueprint
The ranked backlog feeds directly into a costed, phased roadmap and architecture.
AI Strategy and Consulting
The broader engagement discovery belongs to, from baseline to funded plan.
AI Readiness Assessment
A two-week version when you need direction before a full engagement.
What teams ask before they commit a backlog.
Workshops generate ideas; they rarely rank them defensibly. We add the scoring rigor and data validation that turn a long list into a fundable few.
Because without a baseline, you cannot prove ROI even when the system works, a leading reason AI investment loses executive support.
We document why each was retired, so the decision is transparent and revisitable if conditions change. A parked idea is not a lost one.
Yes. Validation is designed to hand straight into delivery, so the backlog is executed rather than re-debated.
Separate the AI ideas that move your business from the ones that just sound good.
You bring the ideas already circulating. We bring the filter, the scoring model, and the data checks that turn them into a fundable few.