Where you are

Your AI Pilot Stalled

The demo impressed everyone. Production never happened. That is evidence, and here is how to read it.

The demo worked. Production has not followed.

The pilot now needs real data, an owner, a security review and a decision about what happens when it gets something wrong. It may also have exposed limits in the model, integration or cost of running it.

The next decision is whether there is a credible route to a useful result.

Establish what stopped it

Name the problem and its owner. Examine the evidence of its cost, the context and data available, technical feasibility, operating costs and the consequences of failure. Separate what the pilot demonstrated from what remains an assumption.

An ownership gap needs an owner. A capability limit may need a different technical approach. Neither diagnosis should be assumed before examining the evidence.

Restart with a test, or stop with a reason

Restart when the problem is worth solving and there is a feasible next test. Agree the owner, baseline, success measure, spending limit and stopping criteria before proceeding.

Stop when the expected value does not justify the cost or risk, or when the evidence rules out the approach. Record what was learned so the next proposal can use it.

We help you make that decision. A real problem and better context improve the basis for a test; they do not guarantee a successful pilot.

Get the pilot an honest reading

Tell me what the pilot was meant to do, who owns it and where it stopped. We can establish what evidence is needed to decide whether to restart or stop.

Not this? The other situations · or just tell me what's happening