Delivery
Build an AI proof of concept that has somewhere to go
· 6 min read
An AI demonstration proves a model can produce an interesting output. A useful proof of concept establishes whether a business should invest in turning that capability into a dependable system.
Demos and proofs of concept optimise for opposite things
A demo is built around the best possible example. A production-minded proof of concept is built to expose uncertainty: weak data, difficult edge cases, integration constraints, unacceptable errors, and the points where human judgment remains necessary.
If your pilot never surfaced anything uncomfortable, it did not test anything.
Start with a decision, not a model
Write the business hypothesis in measurable terms before any build begins: if we apply AI to this defined workflow for these users, we expect this operational measure to improve without exceeding this level of risk.
That sentence is what the proof of concept is testing. Everything else is implementation detail.
Use representative data
The evaluation set should include common cases, difficult cases, missing information, conflicting information, unusual formats, and situations that ought to be escalated rather than answered. A clean sample tells you nothing about production.
Define evaluation before building
Decide up front what you will measure. Depending on the use case:
- Task-completion quality
- Factual correctness and source grounding
- Classification and extraction accuracy
- Tool-use success
- Escalation correctness
- Response time and cost
- User acceptance
Design the human boundary
Decide which outputs are informational, which actions require approval, and which situations the system must refuse or escalate. This boundary is a product decision, not a technical afterthought — and it is what determines whether people trust the system enough to use it.
Test the operational path
A credible proof of concept addresses how the system will authenticate users, access information, respect permissions, connect to tools, record activity and be monitored. These are the things that turn a working prototype into a six-month integration project if they are left until later.
End with a production decision
The output should not be “the demo worked”. It should be one of:
- 01Proceed to a limited pilot.
- 02Resolve specific data or integration gaps first.
- 03Redesign the use case.
- 04Stop, because value or reliability is insufficient.
In short
The best proof of concept reduces uncertainty. It gives decision-makers evidence about usefulness, feasibility, cost, risk and the work required to move forward — including the evidence that tells them to stop.