Assessing two hundred ideas is useful for understanding the shape of the opportunity. It is no way to decide. Many ideas call on the same underlying capability, the same language-model licence, the same knowledge platform, the same productivity tooling, and differ only in who is using it and for what. Submitting them individually understates their value and overwhelms the assessment process in equal measure. So the findings are consolidated, and consolidation is where ideas become business cases.
The unit of decision is the capability
Ideas that share a capability and can be delivered together become a single consolidated use case, which is the unit written up in full and put forward for investment. Two kinds emerge. Cross-business themes, where the same capability recurs in every function: the assistant for drafting and summarising, the knowledge platform, forecasting, market intelligence. And function-specific umbrellas, where a single area’s related ideas are best pursued as one programme: R&D’s on-device work as one research use case wrapping several projects rather than several competing submissions.
In our most recent full programme, 250 ideas consolidated into 27 use cases, eleven cross-business and sixteen function-specific. Nothing was lost: every individual idea stays recorded and traceable beneath the use case it belongs to. The business decides at the level of capability, not the level of the sticky note.
One licence, many benefits
The economics are deliberate. One funded capability returns benefit many times over across the business, and one well-made case is far stronger than a dozen thin ones. A productivity assistant raised by five functions is not five use cases competing for budget; it is one use case whose benefit is the sum of five, whose cost is one licence rollout, and whose case practically writes itself. Consolidation is how the quick wins become obviously fundable.
What a submittable use case contains
| Section | What it answers |
|---|---|
| The problem | In the words of the people who raised it: the pain, how the work is done today |
| The opportunity | What the capability would change, and for whom |
| What it consolidates | Every underlying idea, by reference, with its function |
| The scorecard | Priority, strategic fit, feasibility, complexity, cost band, benefit, risks, data position, vendor options, recommendation |
| Adoption pathway | Research-led, product-led, system-embedded or data-foundation |
| Pyramid layer | Time-to-deploy, so the horizon is explicit |
| Governance fields | Risk category, data protection, human oversight, transparency |
| Owner and stakeholders | Flagged for the business to complete, never pre-filled |
In your format, not ours
Most businesses have an investment or technology-assessment template already. The use case is written to drop into it: the scorecard elements map onto strategic fit, value tree, total cost of ownership and prioritisation matrix; the fields the workshop could not fix are flagged for the owner. The scoring is offered as a recommended straw man for participants to confirm; the formal assessment stays with the business’s own process. Discovery is an input to governance, not a substitute for it.
The roadmap that follows
Consolidated use cases are grouped by readiness, ready now, nearly ready, strategic, research, with the data foundation running underneath. A recommended first quarter follows directly: the governance decision that unlocks the rest, the switch-on wins, the data-in-hand proofs of value, the foundations started in parallel. That is the point at which a leadership team can stop talking about AI and start funding it.
The service is described under opportunity prioritisation and business cases; the workshops that feed it are under AI discovery workshops.