How-To · 1 minute read
How to Run an AI Pilot
To run an AI pilot that succeeds, define success criteria and a business metric up front, use real data and real users rather than a sandbox demo, scope it narrowly to one workflow, and plan the path to production from the start so a successful pilot can actually scale. Most pilots fail not because the AI doesn't work but because they were never built to reach production—no real integration, no evaluation, no scale plan. Run the pilot as the first step of production, not a disposable experiment.
Most AI pilots impress and then die. Here's how to run one that proves value and has a path to production—so it doesn't join the graveyard.
Why pilots fail
Most pilots fail not because the AI doesn't work but because they were never built to reach production—no real integration, evaluation, or scale plan. This is pilot purgatory.
Run the pilot as step one of production
| Do | Not |
|---|---|
| Real data & users | Sandbox demo |
| Success metric up front | "See if it's cool" |
| One narrow workflow | Broad platform |
| Plan to scale | Dead-end experiment |
Treat the pilot as the first step of production, not a disposable demo—the AI MVP discipline.
Define success up front
Set success criteria and a business metric before starting, so you can judge honestly—per how to measure AI success.
Use real data and users
A pilot on clean sandbox data hides the messy reality that breaks systems. Use real data and real users to learn what actually happens.
Plan the path to production
Before starting, know how a successful pilot scales—integration, evaluation, and deployment. See how to scale an AI pilot and how to scope an AI project.
Why FISTA
FISTA Solutions runs AI pilots that reach production—real data, defined metrics, and a scale plan from day one—through its Applied Division and forward-deployed model, backed by 150+ projects across 12+ countries.
Running an AI pilot that ships? Talk to FISTA.
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Questions raised by this field note.
Straightforward guidance for evaluating scope, fit, and the next step.
01How do I run a successful AI pilot?
Define success criteria and a business metric up front, use real data and users, scope to one workflow, and plan for production from the start. Treat the pilot as the first step of production, not a disposable demo, so success can scale.
02Why do AI pilots fail to reach production?
Because they're built as sandbox demos with no real integration, evaluation, or scale plan. When they work, there's no path to production, so they stall in 'pilot purgatory.' Building for production from the start avoids this.
03How long should an AI pilot take?
Typically a few weeks to a couple of months for a focused, single-workflow pilot using existing models. Longer usually signals scope that's too broad—narrow it until you can prove value quickly.
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