As major technology companies invest billions in artificial intelligence, they are systematically eliminating middle management positions, betting that AI can replace human oversight and coordination. Coinbase, Meta, Amazon, and Block have launched aggressive restructuring campaigns that reduce management layers while expanding the workload of remaining managers—a shift that experts warn could undermine worker support, career advancement, and organizational stability.
The trend reflects a calculated gamble by tech leadership: that AI tools can automate managerial functions once performed by humans. Yet the human consequences are becoming visible in real time, as workers report diminished mentorship, reduced access to decision-makers, and mounting pressure on both managers and their teams.
The Scale of the Shift
The restructuring is not limited to a handful of companies. At the end of 2025, openings for middle manager jobs in the US had fallen by 42% compared with a peak in 2022, according to research from workforce data platform Revelio Labs. This represents a dramatic contraction in a career path that once represented stable advancement for millions of workers. Managers comprised 13% of the US workforce in 2022, meaning the current decline affects a substantial portion of the American workforce.
Last week, Coinbase laid off 14% of its workforce while explicitly embracing what the company calls an "intelligence" model, with humans positioned around the edges. The company announced that managers will no longer exist as "pure managers"—instead, all managers must directly contribute code and other work while overseeing 15 or more direct reports, a dramatic increase from the typical six to 12 direct reports that have been standard in the industry.
Block's restructuring has been even more aggressive. After laying off 40% of its workers, some engineering managers were assigned as many as 175 direct reports under its new AI-oriented structure, according to internal organization charts reviewed by the Guardian. This represents a structural experiment without clear precedent in modern management practice.
Who Bears the Burden
The impact falls hardest on workers who depend on managerial support for career development, mentorship, and advocacy. Freeland Abbott, a former technical lead at Square, Block's digital payments service, who was laid off in February, expressed concern that "the more human parts of managers' jobs could slip through the cracks." He warned that "AI cannot provide team motivation, human connection or support in the way a person can," and noted that off-loading employee development to same-level colleagues "could disadvantage less-experienced and marginalized teams."
At Meta, where Prateek Singh worked as a software development manager, the pressures became visible within months of the company's structural shift. After Singh joined in June 2025, managers on certain teams saw their number of direct reports jump significantly. Managers were increasingly expected to write code themselves—a dramatic departure from their previous role of delegating and guiding their teams.
Singh switched his one-on-one meetings with his seven direct reports from weekly to every other week, relying instead on AI agents—bots that execute tasks without human intervention—to collect updates and provide feedback. While the system functioned operationally, Singh observed a critical loss: "people lose touch with all the benefits you get from face time," including mentorship, human judgment and guidance. He left Meta at the end of April, unwilling to remain what he called "a guinea pig" in an unproven experiment.
The Promise vs. the Reality
Tech CEOs frame these changes as efficiency gains enabled by AI. In January 2026, Meta CEO Mark Zuckerberg discussed flattening the company's management structure during an earnings call, suggesting that "projects that used to require big teams now be accomplished by a single very talented person." Amazon CEO Andy Jassy said the company "will need fewer people" doing some jobs. Block's statement from CEO Jack Dorsey and board member Roelof Botha declared: "There is no need for a permanent middle management layer."
Yet researchers who study organizational behavior express significant skepticism about whether these experiments will succeed or should be replicated. Emily Rose McRae, an analyst at Gartner who studies AI's impact on the future of work, warned that the trend will intensify already severe workplace stress: "The middle manager role is about to be under a lot more pressure. What that means for employees is that your job gets harder, too. When your manager doesn't get the support they need, you don't get the support you need."
McRae also noted a structural consequence for worker advancement: "Fewer layers of management means employees will have fewer opportunities to advance. Companies could risk losing important human talent as a result."
The Hidden Costs
Astassia Fedyk, assistant professor at the University of California, Berkeley's Haas School of Business, has studied how AI is changing workforce composition. She found that as AI tools shift work from managers to their reports, "these companies' structural changes could become more permanent," fundamentally reshaping middle management roles and vastly expanding their responsibilities.
The risks extend beyond worker burnout. Singh, reflecting on his experience, warned of potential systemic failures: "If managers are expected to either be writing a lot more code or have a lot more reports, what I see happening is more asynchronous, agent-driven management. Then people lose touch with all the benefits you get from face time." He cautioned that managers under pressure could be "tempted to use AI for decisions and blindly submit flawed suggestions," potentially leading to "data leaks, security holes or even system outages."
Amalia Goodwin, global managing director of the consulting firm Slalom, who focuses on organizational change related to AI, emphasized that simplifying management structures "requires an entire redesign of how work gets done." If more employees are making more decisions, she warned, "they will need the resources, skills and training to be able to judge between good and bad outcomes." Additionally, she noted that "work could slow down in unintended ways"—for example, if one team produces more with AI help, the team approving that work may become overwhelmed.
Skepticism from Management Experts
Matthew Bidwell, a management professor at the University of Pennsylvania's Wharton School, noted that there is a history of companies attempting to break hierarchies with new management forms, but they are "often abandoned or serve as one-offs." He warned that eliminating a management layer removes "a level of necessary scrutiny," adding: "You'll move faster, but you'll break more things, and for some organizations that's probably not the right trade-off."
Raffaella Sadun, a Harvard professor who studies the future of work, noted that tech companies are "very well positioned to make these changes because they're advanced from a tech perspective," but cautioned that "they'll have to incur the cost of change" including overhauling coordination systems, altering decision-making processes, and shifting workers into different positions, including demoting them.
Why This Matters:
The elimination of middle management positions represents a significant structural shift in how work is organized and how workers access support, mentorship, and career advancement. The trend affects hundreds of thousands of workers at a time when middle-class career pathways are already under pressure. The experiment raises questions about whether efficiency gains justify the loss of human oversight, worker development, and organizational resilience. If these restructurings become permanent across industries—as some researchers suggest they may—they could reshape career trajectories for millions of workers, reduce opportunities for upward mobility, and concentrate decision-making authority in ways that may not serve worker interests or organizational stability. The human and institutional costs of this shift remain largely unquantified, even as companies proceed with radical restructuring based on the promise of AI-driven efficiency.