What will most likely happen when companies replace managers with AI

What will most likely happen when companies replace managers with AI

May 29, 2026

I went looking for management training data inside LLMs. What I found - or didn't find - changed how I think about the "replace middle management with AI" conversation.

The training data problem

Every major LLM with a published training mix tells the same story: some domains, especially code, biomedical text, legal text, math, and academic literature, appear as explicit sources or categories. Management usually does not.

Code gets dedicated, curated sourcing. Medicine gets dedicated sourcing. Law gets dedicated sourcing. Management does not appear as a dedicated category in any of them.

Here are the numbers from published model papers and dataset manifests:

(ribbons are not in proportion to the percentages - for illustrative purposes only)

Code has GitHub scrapes, The Stack (3.1TB of permissively licensed source code in 358 languages), and StarCoder's additional 35B Python tokens. Llama 3 allocates 17% of its 15 trillion training tokens to code. Code also has purpose-built benchmarks: HumanEval, MBPP, and others.

Medicine gets PubMed Central at 14.4% of The Pile (EleutherAI's widely-used open training dataset), plus PubMed Abstracts at another 3.1%. Combined biomedical content: roughly 17.5% of that corpus.

Law gets FreeLaw (US case law) at 6.1% of The Pile, plus USPTO patent backgrounds at 3.7%.

Management - no major disclosed pretraining mix contains a dedicated management corpus. No explicit allocation. No canonical, broadly adopted benchmark comparable to HumanEval or MBPP for code. Whatever management knowledge these models have comes from whatever happened to survive Common Crawl web filtering - mixed in with marketing blogs, e-commerce copy, and generic business content. No published study has attempted to quantify the share.

LLMs almost certainly have seen management writing. Management advice, HR policies, leadership books, business blogs, and career guidance all appear somewhere inside broad web and book corpora.

But "management" is not visible as a first-class training category in the major disclosed mixes. Code has GitHub, The Stack, HumanEval, MBPP, and dedicated code models. Medicine has PubMed and PubMed Central. Law has FreeLaw and patent data. Math and reasoning are now explicitly balanced in models like Llama 3. Management, by contrast, is buried inside undifferentiated web, books, and forum content.

That means the evidence supports a narrower claim: current LLMs may contain management knowledge, but there is no public evidence that frontier models were deliberately trained, balanced, and benchmarked for the judgment, contextual awareness, and interpersonal functions that define what managers actually do.

What management actually is

Google ran the cleanest natural experiment on this question. Around 2001, founders Larry Page and Sergey Brin eliminated all engineering manager roles, believing engineers were best left to their own devices. The experiment lasted a few months. Page and Brin were immediately flooded with requests about expense reports, interpersonal conflicts, and project prioritization. Employees complained about the lack of support and guidance.

Google reinstated managers. Then, in 2008, they launched Project Oxygen to understand why managers mattered. They collected over 10,000 observations across 100+ variables. The finding that surprised even Google's VP of People Operations: technical expertise ranked below behaviors such as coaching, communication, empowerment, concern for team members, and career development. What ranked first were relational behaviors of concern and support for employee well-being.

Those are capabilities least visible in disclosed pretraining-source taxonomies and hardest to evaluate with current AI benchmarks.

The "flat org" graveyard

Google is not the only company that tried to remove the intermediary management layer. The pattern is remarkably consistent:

Zappos (2013) adopted holacracy - a system with no managers or job titles. Within weeks, 14% of the workforce (roughly 210 people) accepted a buyout rather than work under the new system. Employees reported confusion about who was in charge, what they were supposed to do, and how compensation worked. By 2023, the company had significantly modified the system, quietly reinstating management functions under different names.

Valve , the gaming company, is famous for its "no managers" culture. Former employees tell a different story. Jeri Ellsworth, a former engineer, described "popular kids that have acquired power in the company." Glassdoor reviews describe needing to belong to powerful in-groups to survive. Academic research (Foss and Klein, 2022, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4289193) concluded that when formal hierarchy was abandoned at Valve, it was replaced by informal hierarchy - invisible,...