"AI disrupting everything" kills the American job market! Layoffs in the technology industry hit a two-year high in May, and computing power budgets are accelerating the replacement of manpower.

The US technology industry announced its largest layoff plan in nearly two years in May. At the same time, tech companies focusing on cutting-edge technology trends are increasing their massive investments in artificial intelligence, highlighting the potential cost of the efficiency and productivity gains brought by the AI intelligence wave ignited by Anthropic in terms of mass layoffs. Anthropic and its leading Claude AI intelligence ecosystem have magnified the market's imagination of "high-salary white-collar knowledge and research work being automated by AI," becoming a narrative catalyst for corporate restructuring, compression of inefficient positions, increased actual productivity, and capital reallocation. Undoubtedly, the "AI disrupts everything" logic is beginning to ignite a comprehensive revolution in enterprise operational efficiency. For example, Block, led by Twitter co-founder Jack Dorsey, laid off over 4,000 employees, nearly half of the total number of employees in the tech company. The company's public statement indicates that the AI agent model of the AI intelligence entity allows smaller teams to maintain higher operational efficiency; its CFO further stated that the efficiency gains brought by the AI agent-centric workflow have led to significant layoffs, which are almost "inevitable" for any company. The pessimistic undertone of the "AI disrupts everything" narrative since February is mainly due to market concerns about the potential weakening of the entire software empire based on the revenue model of SaaS seat subscriptions by phenomena like Claude Cowork and OpenClaw and the viral spread of AI agent workflows. This led to rare sell-offs in software stocks in February and subsequent sell-off trends that quickly spread to industries such as cybersecurity, online education, traditional finance, insurance, real estate, transportation systems, and any other industry that appears to be based on a revenue model of seat subscriptions or labor-intensive business models - the market believes these industries will be completely disrupted by AI and will have to resort to large-scale layoffs to reduce costs and increase efficiency, as well as to accumulate operational capital for the transition to the "AI+" trend, using AI computing resources budgets around cloud AI inference platforms to replace traditional human resources budgets. The AI intelligence tools launched by Anthropic can be said to be the key trigger for the panic selling of software stocks in February, but more accurately, it is not that Anthropic "solely disrupted the entire software stock," but that its Claude agent-based AI tools have made the market suddenly realize that large model companies are radically overturning the enterprise application layer from being "bottom-tier model suppliers," potentially eroding the profit pools of traditional SaaS software companies focused on law, sales, marketing, data analysis, low-code editing, and many other specialized fields. The US technology industry laid off a record high in May, with high-paying white-collar positions bearing the brunt According to statistics from the US career transition services company Challenger, Gray & Christmas Inc., a broad swath of US technology companies disclosed in the past month that they planned to lay off 38,242 positions in May, the largest layoff plan since August 2024. Typically, the actual scale of layoffs in US companies aligns with the layoff plans compiled by Challenger, Gray & Christmas. So far this year, the US technology industry has announced layoffs of 123,653 people, a significant increase of over 65% compared to the same period in 2025. At the same time, in the past five months, the overall number of layoff announcements in the entire US private business sector has unexpectedly decreased by 7% compared to the same period last year, further highlighting the mixed picture of the US labor market, with many industries still in a state of "low hiring, low layoffs." Andy Challenger, Chief Revenue Officer of Challenger, Gray & Christmas, said, "The labor market is being reshaped in real-time by cutting-edge AI technology." "AI is now the primary reason companies give for their layoff plans." These data are in line with the high-profile layoffs related to the AI intelligence wave recently announced by tech companies such as Meta Platforms Inc., the parent company of Facebook, financial software giant Intuit Inc., and Internet era pioneer Cisco Systems Inc. However, despite the abundance of layoff announcements, there has not been a significant increase in the number of unemployment insurance claimants, highlighting that most of these layoffs are concentrated in white-collar positions with relatively generous salaries. Challenger's report shows that although tech companies have announced the largest layoffs in two years, they have also revealed the largest recruitment plans in all industries. However, tech companies' recruitment efforts are generally focused on positions related to AI infrastructure technology and front-line AI deployment projects, and the overall recruitment scale is much lower than in previous years. Data shows that so far this year, employers in all industries in the US have announced plans to hire 80,472 people, an improvement over 2024 and 2025, but still significantly lower than the total for the same period each year from 2019 to 2023. With the AI intelligence wave in full swing, companies are first seeing a significant increase in efficiency in code generation, customer service automation, sales lead processing, document generation, financial compliance, and data analysis. But for macro labor productivity to truly rise, it depends on whether companies have completed process reengineering, data governance, system integration, and organizational restructuring. Therefore, the US technology industry seems to be entering a phase of rewriting its production function with intelligent entities at its core: the decrease in labor demand is for low-value-added, processable positions, while the drivers of rising labor productivity and wage premiums in human society are talents who can manage AI systems, define business processes, and control risks. The monthly US government non-farm employment report, set to be released on Friday, is expected to show that US employers added approximately 85,000 jobs in May, bringing a successful end to the strongest three-month period of employment growth in over a year. From the Anthropic storm to the tech layoffs wave: Companies replace traditional human resource budgets with AI computing budgets The US technology industry's announcement of 38,242 layoffs in May marks the highest number in nearly two years, with a total of 123,653 large-scale layoffs announced so far this year, a year-on-year increase of over 65%. This is strongly correlated with the pessimistic logic and narrative tone of "AI disrupts everything." The AI intelligence ecosystem has magnified the market's imagination of "high-paying white-collar knowledge and research work being automated by AI," becoming a narrative catalyst for corporate restructuring, compression of inefficient positions, increased actual productivity, and capital reallocation. On the other hand, tech companies are focusing their enterprise budgets on AI computing infrastructure, rapid deployment of large AI models, AI security, reasoning resources platforms, and smart product stacks, which is why Challenger's data shows that AI has become one of the primary reasons companies give for layoffs. Anthropic's monthly ARR surged by $110 billion, equivalent to the combined volume of the three major SaaS giants Palantir, Snowflake, and DataBricks over ten years - an unprecedented miracle in the history of capitalism. Anthropic is also projected to see its revenue soar from $48 billion in the first quarter to $109 billion in the second quarter, with operating profits of approximately $559 million, indicating that cutting-edge AI applications are not just consuming computational resources but are beginning to transform enterprise programming, intelligent entity workflows, network security, and data analysis into high-value Token earnings. The surge in demand for Claude and AI tools has propelled Anthropic to its first profitable quarter, with the cost of computing power per dollar of revenue dropping from about 71 cents in the first quarter to about 56 cents in the second quarter, demonstrating an improvement in the economic model of AI applications through economies of scale and reasoning efficiency. This is also why Wall Street financial giant Morgan Stanley has proclaimed that the AI computing arms race is entering a stage of systemic expansion. The institution's capital expenditure expectations for major US tech giants in 2026 have been revised upwards from $433 billion a year ago to $805 billion. Capital expenditures for 2027 are expected to reach $1.1 trillion, up from a previously forecasted $950 billion, and predicted to surpass $3 trillion in AI-related infrastructure investments by 2028, with over 80% of spending yet to come. Mainstream economists' consensus is not that "AI will immediately cause a global wave of unemployment," but that the labor market is entering a period of job restructuring. In the future, the scale of company layoffs will likely exhibit "industry differentiation + position differentiation": tech companies will continue to compress non-core software, support, traditional IT, content production, basic code, and administrative process positions but will also expand positions in AI engineering, data infrastructure, model evaluation, network security, AI product management, computing power operations, MLOps, AI governance, and industry solutions. Challenger's data also shows that although the tech industry has announced the most layoffs, it is also one of the industries with the strongest recruitment plans, indicating that companies are not ceasing to hire but are using AI budgets to replace traditional human resource budgets.