How to run an AI proof-of-concept that doesn't waste a quarter.
Most AI POCs fail before they begin: wrong scope, wrong data, wrong success metric. A POC that can't ship is an expensive demo. Here's how to run one that actually informs the decision.
- Pick a real workflow whose owner cares about the outcome.
- Define success criteria before you start — with the operating team, not the AI team.
- Plan the production path on day one, not after the POC succeeds.
Pick a workflow that matters.
Every operations leader has a list of workflows they'd pay real money to make better. Pick from that list. Don't pick the workflow that's technically interesting; pick the one whose owner is in the room with you and can tell you what success looks like.
If the operating leader can't articulate the cost of doing the workflow badly today, you're not running a POC. You're funding an experiment that no one will defend.
Define success before you start.
Most POCs end with someone subjectively saying "that was cool" or "that didn't work" because no one wrote down what success was. Lock the criteria up front — with the operating team, not the AI team. What does the system have to do? At what accuracy? On what test set? Within what cost envelope? Compared to what baseline?
If you can't answer those questions on day one, you're not ready for a POC. Spend a week answering them first.
Plan the production path.
The most common POC failure mode: the system works in the POC environment and is unshippable in production because of data access, security review, integration, or scale. By the time anyone realizes, the budget for the next phase is gone.
Plan the production path on day one. Get security and legal in the room. Verify data access. Pick architectures that scale to production volumes. The POC is not a science project; it's the first three weeks of an eight-week build.
A 30 / 60 / 90-day outline.
Discover & scope
- Workshop with the operating leader; pick the one workflow.
- Lock success criteria and the eval test set in writing.
- Confirm data access and security review path.
- Sketch the architecture and the production path.
Exit gate: a one-page scope, signed by the business owner, IT, and security.
Build the thin slice
- Ship one end-to-end workflow against real data.
- Stand up the eval harness; run it on every change.
- Bring three to five real users into the loop weekly.
- Instrument latency, cost, citation accuracy.
Exit gate: the system meets or beats the success criteria on the locked test set.
Ship to production
- Limited rollout to one team or location.
- Operational instrumentation; on-call rotation.
- Adoption tracking; weekly read-out to the operating leader.
- Decision: scale, iterate, or stop with what we learned.
Exit gate: live users, measured outcome, named owner for the rollout.
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