The First Batch of Big Tech Employees Laid Off by AI Have Already Returned to Work

Original | Odaily Planet Daily (@OdailyChina)

Author | Golem (@web 3_golem)

The first group of employees laid off by AI have already returned to work.

On February 27, Jack Dorsey’s (founder of Twitter) fintech company Block laid off over 4,000 employees at once, reducing the total staff from 10,000 to less than 6,000. Jack explained the layoffs were due to “AI tools changing everything.” It’s widely accepted that AI will eventually eliminate some jobs, but prioritizing replacing white-collar jobs at the middle and high end has only intensified workplace anxiety. (Related reading: Jack Dorsey’s company, 4,000 white-collar workers being replaced by AI )

However, less than a month later, some of the laid-off employees have already received rehire invitations…

According to Business Insider, these re-employed staff come from various departments, including engineering and recruiting. A design engineer at Block posted on LinkedIn that a leader told him he was laid off by mistake, due to a “clerical error”; an HR person, in a deleted post, said she was re-hired after persistent efforts from her manager; and others reported being mysteriously contacted by Block a week after layoffs and asked to return.

Jack has not publicly responded to the rehire situation. The proportion of re-employed staff is small compared to the original layoffs, but it perhaps already indicates a problem: some roles and tasks are simply not replaceable by AI.

From the cost perspective, employing an enterprise-level AI worker is definitely more expensive than hiring a human.

It costs money to hire people, and tokens to run AI. Claude Opus4.6’s standard base price is $5 per 1 million tokens for input and $25 per 1 million tokens for output; domestic large models are cheaper, with Qwen3.5 plus costing 0.8 yuan per 1 million tokens for input and 4.8 yuan for output.

Take the popular OpenClaw as an example. An internal veteran “shrimp farmer” at Odaily Planet Daily said he used OpenClaw as a life and research assistant for over a month, burning through about $6,000 worth of tokens (using Claude 4.5/4.6 models). $6,000 a month—what kind of top-tier intellectual can’t be hired (except in Europe and America)?

If personal use already costs this much, the cost of integrating AI into enterprise work is even higher. For example, replacing customer service with AI: in some regions with inflated education levels, you can hire a handsome college student for around 3,000 yuan. But training an AI that can truly replace human customer service, handle complex tickets, connect multiple knowledge bases, conduct multi-turn conversations, and operate stably isn’t something that can be covered by just 3,000 yuan a month.

In 2024, Swedish payment company Klarna announced a high-profile layoff of over 1,000 employees, claiming AI customer service could replace the workload of 700 customer service agents. But by May 2025, multiple media outlets including Bloomberg reported that Klarna had started rehiring customer service staff, with the CEO admitting they had “moved too fast” on AI.

Additionally, AI replacing human labor also involves the “Jevons Paradox.”

The Jevons Paradox is an economic concept stating that efficiency improvements don’t necessarily reduce resource consumption—in fact, they can lead to increased total usage because lower costs and higher demand drive up overall consumption. Translated into the AI era workplace, as AI advances improve employee productivity, companies won’t allow employees to rest; instead, they’ll demand more work within the same time frame.

What’s called efficiency gains often turn into a more covert form of workload increase—AI’s supposed liberation of human labor is a complete illusion.

Capitalists also believe that in the AI era, companies won’t need as many employees—like Jack said, “smaller teams equipped with more intelligent tools.” But in reality? After layoffs, companies aren’t simply replacing human workers with AI; remaining employees are taking on more work with AI’s help.

If it’s just about individual tasks, that’s one thing. But fundamentally, a company is a human organization. Wherever there’s organization, there’s “the community,” and AI can integrate into formal organizational structures but will never understand or embed into informal or hidden networks within the company.

So when layoffs happen, it’s not just losing labor; it’s also losing organizational muscle. Remaining employees bear increased workloads and also absorb the anxiety, risks, and responsibilities of their former roles. Fewer collaborators, fewer executors, and most critically, fewer scapegoats.

During Nvidia’s GTC 2026, CEO Jensen Huang criticized companies that use AI-driven efficiency as a reason for layoffs: “Leaders who rely on layoffs to cope with AI are just out of ideas, their minds are already empty. Even with powerful tools, they won’t use them to expand.” That was Huang’s direct quote.

Huang’s point is that AI isn’t here to eliminate employees but to help companies expand and develop new business. Instead of layoffs, they should be hiring more. If management doesn’t realize this, they’re fools. But joking aside, most corporate managers are highly intelligent—they know well the high costs of AI and the ongoing necessity of human labor.

Tech companies’ layoffs may be just a cover; cost reduction is the real goal.

AI has become the universal excuse for tech layoffs. In reality, AI isn’t eliminating individuals but those companies and businesses still stuck in the old era. When a business can’t keep up with AI advancements, leading to stagnating growth and shrinking profits, the AI revolution becomes a new tool for PUA—reducing staff, cutting costs, and pushing more work onto remaining employees. Then, everyone is left to reflect: why weren’t you the one to adapt better to the AI era?

If you’re unlucky enough to hit a critical point, you can always quietly rehire those you laid off. This approach is common in Silicon Valley. After Elon Musk acquired Twitter in October 2022, he laid off about half the staff (over 3,000 people) in early November, then rehired dozens of those who had been cut due to misjudgments or the realization that key roles couldn’t be left vacant.

Back to the present: AI will change many things, but it’s not yet magical enough to compensate for strategic sluggishness, business aging, or lazy management. The story of layoffs and rehires driven by AI, whether due to companies realizing some jobs can’t simply vanish with “AI changes everything,” or just cost-cutting excuses, isn’t inspiring or revolutionary.

It only shows that before the future truly arrives, some have already been hurt by it in advance.