AI opportunity triage in 24 hours

Most organizations are no longer short on AI ideas; they are short on a reliable way to decide which ideas deserve scarce delivery and governance time. BCG found that only 22% of companies have moved past proof-of-concept to generate any value from AI, and only 4% are creating substantial value — the gap is selection and scaling discipline, not access to models.

• The cost of getting intake wrong compounds quietly. Every workflow that enters deep discovery on enthusiasm alone consumes architecture review, stakeholder interviews, and procurement attention that the genuinely high-leverage opportunities then have to wait for.

Without a fixed first-pass gate, prioritization defaults to whoever asked loudest or most recently. Stakeholder time gets allocated inconsistently, follow-up requests become noisy and unfocused, and two similar opportunities can receive opposite decisions depending on who reviewed them.

• Teams also lose the paper trail. When the intake decision lives in a meeting rather than a scorecard, nobody can later explain why one workflow advanced and another was parked — which makes every subsequent governance and budget conversation slower.

Score the workflow bottleneck first: where does the work actually queue, and is that queue expensive in time, money, or risk? A precise bottleneck statement filters out most presentation-grade AI ideas on its own.

• Check for compounding operating advantage, not just generic AI claims. The question is whether the workflow produces feedback data that makes the system better with use, or whether it is a one-off automation that any competitor can copy next quarter.
• Translate every remaining uncertainty into an explicit evidence request with an owner. A triage that ends in "interesting, let us discuss further" has failed; a triage that ends in three ranked questions has done its job.

Use a structured first-pass gate before deeper architecture review, procurement review, or calendar-intensive discovery. The gate should run asynchronously from a short workflow brief, score against a fixed rubric, and return a go-deeper or hold signal inside one business day.

• Treat the output as a handoff artifact, not a verdict: the scorecard plus ranked follow-up questions becomes the agenda for the first deep-discovery session, so the time you do invest starts from evidence rather than from zero.

Collect a workflow brief and operating context asynchronously: who does the work, where it queues, what a unit of throughput is worth, and what systems the workflow touches.

• Score across the fixed rubric — bottleneck severity, value capture, integration readiness, and risk — and record the score next to the evidence that produced it.
• Rank the top follow-up questions by decision impact and assign each one an owner and a deadline. Close the loop by recording the go-deeper or hold decision where the next reviewer can find it.

For low-volume, high-context workflows, manual expert review can still be enough: when one experienced operator sees every request and the request rate is a trickle, a rubric adds ceremony without changing decisions.

• A scorecard is also only as good as its rubric. If the criteria reward demo appeal over operating leverage, structured triage will reproduce the same bad picks faster — revisit the rubric quarterly against the outcomes of past go-deeper calls.