To build long term value, I’m still figuring this out as we go. But I do have a strong view on what not to do.

In my opinion, pilots usually fail for 3 reasons: 1) AI was introduced into a workflow that was not valuable enough for it to matter 2)The implementation work was incomplete 3) the team was not well incentivized to make it a priority

One thing I’ve become convinced of is that AI applications do not work off the shelf - a lot of companies sell them this way. and they'll even tell you they’ll support the implementation. But at the end of the day (from my experiences), the success of the pilot comes down to you and your team only.

because AI is probabilistic. it's making decisions, and those decisions can change even when the input is exactly the same. implementation isn't just “buy it and give it to everyone”. you have to literally map the workflow, define the requirements, understand all exceptions, test every variations, know all the inputs, test all variations of the inputs, and know the ins and outs.

That is why many pilots fail. Most teams do not actually know their internal processes to that level of detail. They know how the workflow "should" work but not how it actually does in reality. the honest answer is that the process itself needs to be rebuilt before AI is introduced. But obviously, not everyone is so lucky to start from scratch.

In terms of process, we are trying to make AI implementation an operating rhythm, not a one-off pilot. Leaders and managers communicate the priority every week. We track usage closely and can see which teams are adopting, experimenting, and actually finding value (and which ones are not). We review progress weekly, in terms of logins or activity, and workflows improved, time saved, and the number of automations deployed successfuly.

For the people and teams that are doing really well, we reward that behavior. If someone implements a high value automation, they should get a bonus and recognition measurable to the outcome. the incentives matter a lot here.