I’ve been thinking about something fairly simple based on what I’ve seen across a few orgs working on AI Enablement.
There’s usually a lot of focus on better models, better tooling, and hiring stronger engineers. That all makes sense.
In practice, those things rarely determine whether anything actually ships or changes how the business runs. Prioritisation tends to matter more. If it’s weak, even strong models don’t lead very far.
Every new idea has to compete with work already in progress, teams that are already allocated, and priorities that have already been agreed on. The question shifts from “Is this a good idea?” to “Is this worth replacing what we’re already doing?”
Most of the time, the answer is no. Changing direction is expensive, so teams stick with existing plans and keep moving.
Curious if others have seen the same thing, or if this has just been specific to where I’ve worked.
I wrote an in depth post about this as well.