This is because they're trying to reduce the wrong headcount. The largest inefficiencies in corpo orgs lie in the ways they organize their knowledge and information stores, and in how they manage decision making.

The rank and file generally have a really good grasp on their subset of the domain -- they have expertise and experience, as well as local context. Small teams, their managers -- those are the ones who actually perform, and deliver value.

As you move up the hierarchy, access to information does not scale. People in the middle are generally mediocre performers, buried in process, ritual and politic. In addition to these burdens, the information systems do their best to obscure knowledge, with the usual excuses of Safe and Secure (tm) -- things are siloed, search does not work, archives are sunsetted, etc.

In some orgs tribalism also plays an outsized role, with teams acting competitive, which largely results in wasted resources and seven versions of the same failed attempt at New Shiny Thing.

Then as we look higher yet in the hierarchy, the so-called decision makers don't really do anything that cannot be described as "maximize profit" or "cut costs", all while fighting not to get pulled down by the Lord of the Flies shenanigans of their underlings. They are the most replaceable.

A successful "AI Transformation" would come in top-down, going after the most expensive headcount first. Only truly valuable contributors would remain at that level. Organizational knowledge bases would allow to search, analyze and reason about the institutional knowledge accrued in corporate archives over the years, enabling much more effective decision making. Meanwhile, the ICs would benefit from the AI boost, outsourcing some menial tasks to the machine, with the dual benefit of levelling up their roles, and feeding the machine more context about the lower-level work done across the org.