Your AI Pilot Worked. Should You Kill It Anyway?
About this session
Most AI pilots are designed to answer one question: can we make this work? But a successful pilot does not automatically mean it should be scaled.
Strong technical results, positive user feedback, and an enthusiastic sponsor can make scaling feel like the obvious next step. Yet the pilot may tell us very little about what it will cost to run, how it will fit into existing workflows, whether the value holds at scale, or whether it is still the best use of investment and engineering capacity.
In this interactive deep-dive session, we will work through different realistic AI pilots and examine the decisions that come after a successful pilot. As new information emerges, the audience will be asked to reassess which initiatives deserve to move forward, which need to change, and which should stop.
The focus is not on how to run better pilots. It is on how leaders decide which successful experiments are actually worth scaling.
Because pilot success is evidence. It is not a business case.
Speaker
Key takeaways
- How to separate technical success from operational readiness, business value, and strategic priority
- A practical way to assess whether an AI initiative is ready to scale
- How to compare promising AI initiatives when funding, engineering capacity, and leadership attention are limited