By the first quarter of 2026, the tech industry has already witnessed the loss of over 30,000 jobs. Amazon recently slashed 16,000 corporate positions to introduce AI agents, and Meta also laid off over a thousand employees from its AI division, aiming to "streamline" operations.
Crypto.com CEO Kris Marszalek stated that companies failing to integrate AI into their operations will be left behind by the times. This 12% layoff is specifically targeting roles deemed unsuitable for their new AI-driven workflows.
However, following these large-scale layoffs, several employees have shared experiences of being almost immediately rehired. For instance, Richard Hesse, a 15-year veteran at Block, had to spend days convincing management that he alone could not maintain the "highly critical" infrastructure for Square and Weebly clients. Eventually, some of his former colleagues were offered re-employment.
Discussions surrounding these layoffs often focus on whether AI can truly replace these workers or if it's merely a convenient excuse for management missteps. According to Cryptopolitan, Jack Dorsey admitted to issues in building the independent architecture for Square and Cash App between 2019 and 2022, a period during which the company's headcount tripled.
Employees Return to Work After AI-Related Layoffs
Companies actively embracing the AI integration wave are gradually realizing that while AI can write code and organize data, it currently cannot manage the infrastructure that supports the complex operations of large enterprises. IBM's Arvind Krishna confirmed that efficiency gains from AI allow the company to reinvest resources into labor-intensive areas like software engineering and sales.
Similarly, Klarna CEO Sebastian Siemiatkowski admitted the company is reassessing its strategy after initially claiming its AI assistant could replace 700 full-time employees. Home renovation platform Livspace also rescinded its decision to lay off 25% of its workforce (approximately 1,000 people) in February 2026 to implement an "AI-native" model.
These cases indicate that despite AI's potential in certain areas, deep human involvement and judgment are still required for handling complex business processes and infrastructure management. The industry continues to observe and discuss the extent to which AI can truly achieve substitutive work efficiency and its long-term impact on the job market.