The pyramid-shaped organizational structure of modern companies exists, at its core, to overcome the limits of human IO bandwidth.
There is a cap on how much information a person can process and how many people they can directly manage. That's why companies need layer upon layer of managers, who continuously aggregate, compress, and abstract information from below and pass it up to decision-makers at the top.
The entire management hierarchy is, in essence, an information compression and transmission system.
But AI changes this fundamental assumption.
At the scale of enterprise management, AI can process massive amounts of information simultaneously, directly integrating data from different departments, projects, and employees without going through layer after layer of manual reporting.
This means that the many management layers that existed to overcome the human I/O bottleneck may no longer be necessary.
Of course, decision-making, accountability, and incentives still need to be borne by people, but the transmission and integration of information no longer needs to rely on a pyramid.
Future companies may no longer be pyramids of layer-by-layer reporting, but flat organizations composed of a small number of decision-makers, specialized executors, and AI coordination systems.
There will no longer be so many layers of manager-directors-VP-CXO-CEO.
These so-called middle managers will all lose their jobs.
Information integration is getting faster, but much of what middle managers do—setting goals, resolving conflicts, developing people—is still an open question for AI. To really test this, you could start with a small pilot in one department: cut out a layer of reporting, see how decision speed and employee feedback change, and only then talk about large-scale flattening.