Can't justify the compute? Give it the boot!

One of the most common things we see when we start working with a business that's new to AI is a graveyard of half-running pilots. A chatbot that sort of works. A summarisation tool that people use occasionally. An automation nobody's really sure is saving time. All still live. All still consuming someone's attention. None of them delivering much.

It sounds counterintuitive, but this cautious, hedge-your-bets approach to AI adoption is actually one of the riskiest things you can do.

Run many. Run cheap. Run short.

If you're just getting started with AI, you should absolutely be running multiple pilots at once. The goal is to find what actually moves the needle for your business, not to read about what works for someone else's. So explore broadly. Keep each experiment low-cost and low-effort. We're talking days of setup, not months. And run them short.

But here's the bit most people skip: before you start, agree on what success actually looks like.

Not vague success. Specific success. Does it save two hours a week per user? Does it increase throughput by 20%? Does it cut error rates in half? Whatever the metric, write it down, agree it with the relevant people, and set a time window. Four weeks. Six weeks. Whatever's appropriate. Then check.

If it's not working, kill it.

Not pause it. Not give it another month. Turn it off, document what you learned, and move on.

This is where most businesses bottle it. Nobody wants to be the person who pulled the plug on the AI initiative. It feels like failure. But a pilot that doesn't meet its success criteria is a failure, and pretending otherwise is where the real damage happens.

The slow burn is the real threat.

A pilot that's clearly failing gets killed. A pilot that's limping along, not quite delivering but not obviously broken, is a different beast entirely.

It keeps consuming time. Someone has to maintain it, monitor it, answer questions about it, explain why it hasn't been rolled out yet. It takes up a slot in every AI update meeting. It becomes the thing you're 'keeping an eye on'. Meanwhile, your team's enthusiasm for AI, which is finite and hard to rebuild once it's gone, starts to quietly drain away.

Worse, it starts to shape your strategy. You hold back on the next thing because you're waiting for this one to resolve. You can't tell stakeholders whether AI is working or not because the evidence is mixed and unclear. The fog of inconclusive pilots is one of the most effective ways to derail an otherwise sensible AI strategy.

Failure is fine. Limbo is not.

To be clear: we're not saying be reckless or write off experimentation at the first sign of trouble. Some pilots need time to embed. Some need iteration. That's expected and normal. Around 80% of AI projects fall short of their initial productivity goals, so you should absolutely bake in review cycles that capture learning rather than assign blame.

But there's a difference between iterating on a pilot that's showing real promise and flogging one that's going nowhere because nobody's quite ready to make the call. The pre-agreed success criteria are your friend here. They take the politics out of it. Either the numbers are there or they aren't.

Run the experiment. Check the numbers. Be honest. Move fast.

The businesses we see making real progress with AI aren't the ones who've found the perfect tool on the first try. They're the ones who've run ten cheap experiments, killed seven of them quickly, learned from all of them, and doubled down on the three that actually delivered.

Ready to build a pilot framework that actually works?

If you're trying to figure out where to start, how to structure your experiments, or how to set meaningful success criteria for AI in your business, that's exactly what we work through with clients as part of an AI Readiness Diagnostic. We identify the right use cases, build in the right metrics, and make sure you're not still talking about the same three pilots in six months' time.

Get in touch or book a discovery call. Happy to have a natter about where you are and what would actually be useful.