Service
AI opportunity assessment
Most organizations have more AI ideas than capacity to execute them, and no comparable way to choose between them.
Teams generate long lists of automation ideas, and effort goes to whichever idea has the loudest sponsor, not the one with the highest return.
By year end, leadership cannot say which pilots earned their budget and which quietly absorbed engineering time without producing anything measurable.
Method
What we do
Inventory every proposed and in-flight use case
A single list, not five spreadsheets owned by five different teams.
Score each on cost to build, cost to run, and value at scale
The same scoring model applied consistently, so ideas can actually be compared.
Rank them on one comparable scale
Not three separate rankings that never get reconciled.
Deliver a sequenced roadmap with go and no-go thresholds
What gets built first, and what has to be true to build the next one.
Set the metrics each pilot must hit before scaling
Defined before the pilot starts, not argued about after.
Deliverables
What you get
- A prioritized, scored use case registry
- A 12-month sequencing roadmap
- Go and no-go criteria for each use case
- An executive summary written for the board
Logistics
Typical engagement
| Duration | Participants | Format |
|---|---|---|
| 3 to 4 weeks | Business unit leads, finance, IT | Structured interviews, working sessions, and a written assessment |
Who this is for
- You have more AI ideas than capacity to execute them
- You have budget approved but no ranking method
Who this isn't for
- You have a single, already-validated use case ready to build. Start with workflow automation instead