Strategy · Dec 2025 · Ade Ayorinde

Why AI pilots stall, and what to do instead.

I keep seeing the same pattern. A company announces an AI strategy. A cross-functional team is assembled. They identify use cases, run a pilot, build a proof of concept. The demo goes well. Leadership is impressed. Then nothing happens.

Six months later the pilot is still a pilot. The team has moved on to other priorities. The proof of concept sits in a staging environment that nobody maintains. The company announces a new AI initiative and the cycle starts again.

I've seen this play out across multiple teams and business units. The problem is never the technology. It's always the same three things.

First: the pilot was never scoped for production. Proof of concepts are designed to prove something is possible. Production systems are designed to be reliable, maintainable, and integrated into existing workflows. These are fundamentally different briefs with different requirements, different timelines, and different stakeholders. Most pilots skip the boring questions, who owns this when it's live? How does it handle errors? What happens when the data changes?, because those questions make the timeline longer and the demo less exciting.

Second: there's no product owner. AI initiatives get sponsored by a senior leader and staffed by whoever's available. Nobody's job is to take this thing from experiment to operating capability. Without someone accountable for adoption, integration, and iteration, the pilot is an orphan the moment the demo is over.

Third: success is measured in impressiveness, not impact. The pilot that wows in a boardroom is not always the one that saves the most time or money. The most valuable AI applications I've shipped have been deeply unglamorous, data cleaning, report generation, document triage. They didn't make good demos. They made good businesses.

The fix is to stop treating AI as a special category. Treat it like any other product initiative. Define the problem. Scope for production from day one. Assign an owner. Measure outcomes, not outputs. If you wouldn't ship a feature without a product manager, don't ship an AI workflow without one either.

Have something to deliver?

Tell us the outcome you need. We will tell you whether it needs AI, and how we would get there.

Start a conversation