Altman admits mistakes, Amodei changes his tune: Is the AI unemployment panic a cry of "wolf"?

Among the AI giants, "doomsday" is out of style, and "prosperity" is making a comeback.

A year ago, OpenAI CEO Sam Altman was publicly warning that a large number of jobs would "completely disappear."

Anthropic CEO Dario Amodei asserted that within five years, half of entry-level white-collar jobs would cease to exist, and the unemployment rate could soar to 20%.

Palantir CEO Alex Karp even declared that in the age of AI, only artisans and those who are naturally unconventional in their thinking could ensure they wouldn't be eliminated.

At that time, from Elon Musk to the leaders of traditional automotive giant Ford, everyone was painting a bleak picture of AI devastating office white-collar workers.

However, this "jobs doomsday" narrative has abruptly come to a halt.

Altman readily admitted his mistake. Amodei changed his tune, no longer talking about job displacement but instead about how AI could increase human productivity tenfold. Musk simply stated that in the future, work won't be a necessity but more of a personal hobby.

Their sudden change of heart is driven by multiple pressures.

Not only do they need to tell a good story for an IPO rush, but public negative sentiment toward AI has become unbearable. On top of that, employment data shows no signs of a "doomsday" scenario, and the actual cost and performance of AI are far from what was hyped.

01 From "Doomsday Prophecy" to "Productivity Myth"

At the end of May 2026, Altman publicly reflected at an industry conference in Sydney, admitting that the industry had underestimated the core value of "people" in economic interactions. He acknowledged that the widespread disappearance of white-collar jobs he had previously envisioned did not occur and that his intuition about AI's economic impact was wrong.

Amodei also revised his radical views, shifting to define AI as a "productivity multiplier."

In May, when he shared the stage with JPMorgan Chase CEO Jamie Dimon, he suggested that even if 90% of workflows were automated, the remaining 10% would generate new labor demands, and individual productivity could instead multiply several times.

In an article published in June, Amodei explained the reason for his change of heart: his earlier warnings were meant to better prepare policymakers, and he never intended to be a "doomsday prophet." Still, he left some room, stating that the risk of "persistent unemployment" remains.

Ford Motor's practices reflect this shift. Ford CEO Jim Farley predicted last year that AI would replace nearly half of U.S. white-collar workers, but recently the company reversed course and expanded hiring by hundreds of engineers, citing the need for engineers with deep technical expertise to ensure the quality of automation tools.

Goldman Sachs CEO David Solomon pointed out from a historical cycle perspective that from electrification to the digital revolution, every technological disruption in the U.S. has been accompanied by the birth of a new employment ecosystem. Research from the institution shows that just AI-driven data center construction has created 200k jobs since 2022.

Nobel laureate in economics Daron Acemoglu's research also confirms that the substitution effect of AI is typically offset by new labor demands brought about by productivity improvements.

Fintech company Ramp, in collaboration with workforce intelligence firm Revelio Labs, tracked AI investment and hiring data for nearly 22k U.S. companies.

The report shows that "high-intensity adopters" of AI (companies with per-employee monthly AI spending exceeding $30) saw employee growth rates as high as 10.2%, with growth spanning engineering, sales, administration, finance, and other positions.

This phenomenon confirms the "Jevons paradox" in economics, where technological improvements that increase resource efficiency lead to increased, not decreased, consumption.

Box CEO Aaron Levie and Apollo's Torsten Slok both noted that AI reduces the unit cost of core outputs like coding and customer interaction, which in turn incentivizes companies to expand their business boundaries, thus boosting overall labor demand.

Another set of macro data from Goldman Sachs shows that over the past year, AI has net eliminated about 16k jobs per month, with Gen Z and entry-level employees bearing the brunt. However, at the forefront of technology, entry-level headcount actually grew by 12% at top companies.

This subtle contradiction reveals a harsh reality: AI is creating polarization. Fast-moving tech frontier companies are expanding hiring, while most traditional enterprises stuck in experiments and lacking sustained investment are hardest hit by job losses.

02 Paving the Way for the IPO

Given that the impact on the job market is so complex and volatile, why have these tech luminaries changed their rhetoric so quickly?

Currently, OpenAI is preparing to confidentially file for an initial public offering (IPO), with a target valuation of $1 trillion and plans to raise at least $60 billion, aiming for $280 billion in revenue by 2030. Meanwhile, Anthropic has also submitted a confidential S-1 filing, with its valuation approaching the trillion-dollar mark.

AI strategy consultant Bob Hutchins pointed out that companies cannot go to public markets with a narrative of "social collapse and mass unemployment" to win the trust of bankers and retail investors. Faced with upcoming compliance reviews and IPO fundraising, these giants must adjust public expectations.

He explained that in 2025, CEOs were speaking to tech media, where bold statements were welcomed. But by 2026, their audience shifted to bankers, retail investors, and ordinary people who are already fed up. The audience was no longer buying it, so the rhetoric had to change as well.

Additionally, public negative sentiment toward AI is building.

An NBC poll shows that the net positive rating of AI has turned negative. A Gallup survey also indicates that younger generations are increasingly anxious and resistant to AI, even sparking offline protests against data center construction and tech executives.

Even if the warnings about job losses were well-intentioned, they directly clashed with a population already suffering from job anxiety.

When ChatGPT was released and talk of job displacement emerged, it coincided with a wave of massive layoffs in the tech industry following years of over-hiring. Further warnings from executives about job losses precisely hit an already exhausted workforce. These warnings conveniently became the perfect excuse for corporate layoffs: cutting jobs was framed as an inevitable step aligned with the technological wave.

David Autor, an economics professor at MIT, bluntly stated that tech moguls have realized that claiming their great new product will destroy the social economy is extremely bad business marketing. In the process of promoting data center construction and dealing with government regulations, downplaying fears of unemployment has an inevitable political intent.

Business-level ROI anxiety has also forced companies back to reality. A survey by Emergn shows that most U.S. business leaders struggle to see a real return on their AI investments.

At the same time, high computing costs are creating bottlenecks for technology adoption. Bryan Catanzaro, Vice President of Applied Deep Learning at NVIDIA, revealed that in certain projects, "computing costs have far exceeded employee costs." Giants like Uber and Microsoft, due to excessive budget consumption, have begun to tighten or cancel some AI tool usage licenses for engineers.

03 AI Becomes an Accomplice to Layoffs

Despite the optimistic shift in narrative from the bigwigs, the wave of layoffs in the tech industry continues.

In the first five months of 2026, tech industry layoffs have already exceeded 115k. Data from Challenger, Gray & Christmas shows that AI has been cited as the reason for layoffs for nearly 50k jobs.

Andy Challenger, a workplace expert at Challenger, Gray & Christmas, said that the essence of layoffs is not jobs being completely replaced by AI, but rather a shift in corporate capital allocation. Budgets originally intended for human compensation are being redirected to purchase computing power and servers.

Notably, among companies that previously cut customer service positions citing AI, about half have already planned to rehire human workers due to automation quality issues. This proves that AI's substitution capability at this stage has been significantly overestimated.

The discussion about AI's impact on employment has swung violently over the past four years, from the "efficiency myth" to the "unemployment doomsday," and now back to "returning to rationality."

In this round of narrative correction, the most specific footnote comes from Altman's own small experiment. Altman tried using an AI agent to reply to his daily Slack and email messages, but eventually gave up due to the lack of real human traits and emotional connection, opting to return to manual replies.

This small episode in tech history shows that no matter how algorithms evolve, the core of business society and economic collaboration remains "human-to-human interaction." Trust, intuition, and emotional resonance in complex business environments are still barriers that cold codes cannot cross.

Source: Tencent Technology

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