Use AI to flatten middle management this year?
AI agents allow teams of 14 engineers to run with three, but expanding managerial spans of control up to 175 risks system outages and exposes organizations to massive waste from fabricated workflows.
The question
Big tech is publicly using AI as the rationale to flatten management layers. Do we follow — increasing span of control, cutting one layer, redeploying managers as ICs — or hold the org chart and absorb productivity gains elsewhere?
Counsel's position
Pilot AI-driven flattening in contained areas, carefully re-skilling managers for high-value IC roles, rather than a blanket organizational change.
Verdict
The verdict: Pilot AI-driven flattening in contained areas, carefully re-skilling managers for high-value IC roles, rather than a blanket organizational change.
How the criteria decide
3 of 3 criteria resolved on cited evidence.
| Criterion | Favours | Evidence |
|---|---|---|
| AI productivity gains and management-layer trade-offs | Flatten management layers | AI agents allow teams of 14 engineers to run with three Teams that once had 14 engineers now run with three. Their internal tool, BuilderBot, autonomously ships features to production. Companies reinvest AI gains while 17% cut headcount our data suggests that only 17% of companies are using AI gains to be able to cut headcount. For every one company cutting and reducing their headcount, more than twice as many are reinvesting in their people. |
| Span-of-control + org-shape decisions | Hold the org chart | AI-expanded spans of control up to 175 risk system outages managers, under increasing pressure, are tempted to use AI for decisions and blindly submit flawed suggestions. That could compound as other teams build on top of those decisions and could lead to data leaks AI (artificial intelligence) | The Guardian Middle managers resist AI transparency to protect fabricated workflows The most valuable information that we can bring into the enterprise will improve margins by revealing the massive waste caused by Slurm. |
| Reversibility and reputational risk in AI-driven org changes | Hold the org chart | AI-expanded spans of control up to 175 risk system outages managers, under increasing pressure, are tempted to use AI for decisions and blindly submit flawed suggestions. That could compound as other teams build on top of those decisions and could lead to data leaks |
AI-expanded spans of control up to 175 risk system outages
Pushing managers to oversee drastically larger teams via AI agents degrades human oversight and increases the likelihood of flawed, automated decision-making.
AI agents allow teams of 14 engineers to run with three
Rebuilding around small squads augmented by internal AI tools breaks the traditional correlation between headcount and output.
Middle managers resist AI transparency to protect fabricated workflows
AI exposes the massive organizational waste maintained by middle management, prompting fierce resistance from those whose jobs depend on the status quo.
Companies reinvest AI gains while 17% cut headcount
Despite public narratives about layoffs, the majority of companies are using AI efficiency gains to reinvent their workforce rather than cut staff.
Read another verdict
- Start with a small test, or take on the whole process at once?
- Our competitors advertise AI and we don't — match them, or hold the line?
- Our people already put client files into ChatGPT — ban it, frame it, or supply a tool?
- Our most experienced person retires in two years — how do we keep what they know?
- We can't hire the experienced people we need — automate, train up, or outsource?
- Slow our EU AI Act prep now the deadline's moved to 2027?
- Let an AI agent act on its own — or keep a human in the loop?
- Invest in pre-build costing or post-deployment ROI tracking?