AI Use Case Triage

ai-use-case-triage

Most AI adoption stalls not from lack of ideas but from too many, all sounding equally promising. This produces a ranked portfolio with rejections: what to do first, what to hold, and the condition that would move a held item onto the list.

A triage that promotes everything has triaged nothing. The not-yet list is the deliverable's spine.

How to respond

1. Inventory the candidates. From whatever the user brought — a brainstorm, a backlog, interview notes. Each candidate is stated as a workflow and a person, not a technology: ✅ "Support agents drafting first-response replies" — ❌ "Use LLMs in support." If a candidate is a technology looking for a job, say so and either recast it or drop it.

2. Score each on three axes, 1–5, and show the weights. Default weights: value 40 · feasibility 35 · risk 25. State them, and restate them if the user's context justifies different ones (a regulated environment legitimately weights risk higher). Hidden weights make a ranking an opinion.

   • Value — time recovered, quality lifted, or revenue/cost moved. Quantify where the input allows; mark directional where it doesn't. Never invent a number.
   • Feasibility — is the input data reachable, is the output checkable, does the workflow already have a review step? A task whose output nobody can verify is not feasible, however easy the prompt.
   • Risk — blast radius if the output is wrong and someone acts on it. Score the consequence, not the technology's reputation.

3. Rank, then sanity-check the top. The highest score wins only if its failure is survivable and visible. A high-value, high-risk item where a wrong answer reaches a customer unreviewed is not a first slice, whatever the arithmetic says — demote it and say why.

4. Name the first slice, and what it proves. One use case, with the observable that would confirm or kill the thesis and a time box. ✅ "Draft first-response replies for the top 3 ticket categories; the thesis dies if agents edit more than half the draft body after 4 weeks." A first slice with no kill condition is a pilot that runs forever.

5. Write the not-yet list with promotion conditions. Every rejected candidate gets one line saying what would change the answer — "when the knowledge base is deduplicated", "when a human review step exists in the workflow". A rejection with no condition reads as a permanent no and gets re-litigated next quarter.

6. Hand off. The first slice's economics → business-case; how success will be measured → success-metrics; how it reaches people → ai-adoption-rollout; whether the output can be evaluated at all → llm-eval-harness.

Quality bar

• The weights are shown and justified in one line. A ranking with hidden weights is an opinion wearing a table.
• Every score has a one-line reason. A bare 4 is not a judgement anyone can challenge.
• The not-yet list is non-empty, and every entry carries a promotion condition. If nothing was rejected, the triage didn't happen.
• Each candidate names a workflow and a person, not a technology.
• The first slice has a kill condition with an observable and a time box.
• Unknown numbers are marked directional, never invented — a fabricated ROI figure poisons every decision downstream.

When to use this skill

• ✅ More AI ideas than capacity, and the team needs a defensible order.
• ✅ "Where should we start with AI?" from a leader who has heard a dozen pitches.
• ✅ Re-triaging a stalled portfolio where three pilots are half-running.

When NOT to use this skill

• ❌ Assessing whether the organisation can adopt anything yet — that's ai-readiness-assessment.
• ❌ Pricing one option properly (build vs buy, Option 0, cost layers) — that's business-case.
• ❌ Planning the human rollout of a chosen use case — that's ai-adoption-rollout.
• ❌ Writing requirements for the thing you picked — that's prd-draft.

Anti-patterns to avoid

• ❌ A portfolio with no rejections. Ranking ten ideas 1–10 and calling it a roadmap is capacity denial, not triage.
• ❌ Scoring the technology instead of the workflow. "RAG: 5/5" is not a use case. The unit is a person doing a job.
• ❌ Invented value numbers. A confident "$400k/yr saved" with no source is the single fastest way to lose a room that includes a finance lead.
• ❌ Ignoring verifiability. Feasibility is not "can a model produce this?" — it is "can someone tell whether it's right, before it matters?"
• ❌ A first slice that can't fail. If no observable would kill it, it isn't a pilot; it's a commitment with a pilot's label.

Non-interactive: with no user to ask, use the default weights and tag them [assumption]. If the input contains no candidate use cases — only a general request to "use AI" — emit BLOCKED: need at least three candidate workflows to triage rather than inventing a portfolio.