[lucumo]

> Sounds like every AI KPI I've seen. They are all just "use solution more" and none actually measure any outcome remotely meaningful or beneficial to what the business is ostensibly doing or producing.

This makes more sense if you take a longer term view. A new way of doing things quite often leads to an initial reduction in output, because people are still learning how to best do things. If your only KPI is short-term output, you give up before you get the benefits. If your focus is on making sure your organization learns to use a possibly/likely productivity improving tool, putting a KPI on usage is not a bad way to go.

[sarchertech]

We have had so many productivity improving tools/methods over the years, but I have never once seen any of them pushed on engineers from above the way AI usage has been.

I use AI frequently, but this has me convinced that the hype far exceeds reality more than anything else.

[voidhorse]

> organization learns to use a possibly/likely productivity improving tool

But that's precisely the problem with not backing it with actual measures of meaningful outcomes. The "use more" KPIs have no way of actually discerning whether or not it has increased productivity or if the immediate gains are worth possible new risks (outages).

You don't need to run cover for a csuite class that has become both itself myopic and incredibly transparent about what they really care about (cost cutting, removing dependencies on workers who might talk back, etc.)