The End of Experiments: Why AI Pilots No Longer Cut It

Most AI projects start with a bang and end with a slide deck. The model worked. The demo landed. The dashboard looked sleek. But nothing changed. The team went back to their old habits, the decisions stayed the same, and the "pilot" quietly drifted into the graveyard of innovation theatre.

This is the problem: organisations treat pilots as progress. In reality, they’re often permission to delay real change. Pilots are low-risk, low-commitment, and politically palatable. But they’re also where AI initiatives go to die.

What’s changed is context. “Over 65% of companies now use GenAI across functions”. (McKinsey, 2024).

AI is no longer novel — it’s table stakes. The firms moving fastest aren’t running tests. They’re rebuilding workflows. They’ve moved past proving the tech and into designing for adoption, accountability, and return.

If you’re still piloting, you’re not learning — you’re hesitating. Worse, every stalled pilot erodes organisational trust in AI. And with everyone moving around you? Everything means going backwards. Not fast enough growth is sending you backwards. Standing still is sending you backwards. But, don't worry, two negatives... Stay as a negative. That sends your "pilots" backwards even further.

In no time at all, people stop believing it will ever land.

Here’s the shift: treat pilots like validation checkpoints, not destinations. Define up front what success means, who owns it post-pilot, and how it gets operationalised. If you can’t name the decision AI will change or the behaviour it will influence, don’t launch it.

Pilots don’t create impact. Operations do. The companies that break through are the ones who stop experimenting and start embedding.