Use AI to flatten middle management this year?
AI-driven management flattening risks degrading mentorship and product quality, even as only 17% of companies use AI productivity gains to cut headcount, creating organizational congestion if traditional review cycles remain.
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
Selectively flatten management layers in areas where AI demonstrably augments individual contributor autonomy, while preserving essential leadership and investing in new manager development.
Verdict
The verdict: Selectively flatten management layers in areas where AI demonstrably augments individual contributor autonomy, while preserving essential leadership and investing in new manager development.
AI-driven management flattening risks degrading mentorship and product quality
Given your decision on whether to increase span of control, note that replacing human management with AI agents can create severe operational risks.
Individual AI productivity gains create congestion in traditional decision pipelines
If you hold the org chart, recognize that faster individual output will bottleneck at existing managerial review layers.
Block restructured 40% of its workforce around small AI-augmented squads
As you consider cutting layers, observe how Block broke the headcount-equals-output paradigm by integrating internal AI tools.
AI exposes and eliminates fabricated inefficiencies managed by mid-level managers
When deciding whether to cut management layers, consider that AI's transparency naturally targets roles built around maintaining unnecessary processes.
Only 17% of companies use AI productivity gains to cut headcount
Before following the narrative of AI-driven layoffs, note that the majority of enterprises are absorbing productivity gains to reinvent their workforce.
Read another verdict
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- Our best people's know-how isn't written down — can AI even use it?
- Automate this workflow, or redesign it before we automate?
- Which process should we point AI at first?
- Our AI pilot works but nobody uses it — fix the workflow or kill it?
- Rent AI from a vendor, or run your own?