AI Diagnostic & Use-Case Assessment · Asset Pack
Sequencing beats model choice. Picking the wrong model costs a rebuild; picking the wrong scenario costs a quarter.
Turns "we should do AI" into a prioritized, actionable list.
The diagnostic framework starts from business workflows, ranks candidate use cases by ROI and feasibility, and produces a one-page priority matrix plus a 90-day roadmap. Built for companies assessing AI opportunities systematically for the first time — or leadership teams forced to choose between competing department requests.
If you are hitting these
- You know you need AI, but not where to start, how much to invest or how soon to expect results
- Leadership has no shared yardstick for evaluating AI investments
- Departments have submitted a batch of requests and you can't tell which comes first
You already have one scenario with agreed acceptance criteria — you need to build, not to rank.
How to use it
The full path from inventory to acceptance; each step has a concrete output.
What's inside
Opportunity scoring worksheetPriority matrix template90-day roadmap skeletonEvery deliverable in the pack — apply as-is, then adapt to your business.
List 5–10 candidate points in your workflows that are repetitive, rule-based and data-backed.
Score on the three worksheet dimensions, flagging items that lack data.
Position each use case on the ROI × feasibility quadrants.
Plan validation windows and acceptance questions for the do-first quadrant.
Acceptance standards
You've used this pack well when the following hold — they double as review criteria.
- 01
Every shortlisted use case can answer: which data, who uses it, how much time it saves
- 02
The priority matrix is confirmed by both the business owner and finance
- 03
The 90-day plan includes explicit validation windows and stop conditions
Output template preview
A skeleton of what the pack produces; the full template ships inside the pack.
- Support ticket routing (data: 2 yrs of tickets)
- Lead pre-screening (data: CRM records)
- Quoting agent (no historical quote data)
- Note: re-evaluate once the workflow stabilizes
Dashed rules mark example rows — replace them with your own data and the sheet is done.
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AI Diagnostic & Use-Case Assessment · Asset Pack
- Our stance
- Sequencing beats model choice. Picking the wrong model costs a rebuild; picking the wrong scenario costs a quarter.
- If you are hitting these
- You know you need AI, but not where to start, how much to invest or how soon to expect results; Leadership has no shared yardstick for evaluating AI investments; Departments have submitted a batch of requests and you can't tell which comes first
- When not to use it
- You already have one scenario with agreed acceptance criteria — you need to build, not to rank.
The copied text carries the source link — safe to drop into an internal doc, mail, or meeting note.
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