KPIs are just plausible denyabily in a can.
In my experience, KPIs that remain relevant and end up pushing people in the right direction are the exception. The unethical behavior doesn't even require a scheme, but it's often the natural result of narrowing what is considered important.If all I have to care about is this set of 4 numbers, everything else is someone else's problem.
It's part of the reason that I view much of this AI push as an effort to brute force lowering of expectations, followed by a lowering of wages, followed by a lowering of employment numbers, and ultimately the mass-scale industrialization of digital products, software included.
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.
I use AI frequently, but this has me convinced that the hype far exceeds reality more than anything else.
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.)