The tech industry is experiencing an AI-driven wave of layoffs, with giants like Oracle and Amazon significantly reducing jobs.
According to the latest industry reports and enterprise disclosure documents, by 2026 the technology sector is experiencing a wave of large-scale layoffs driven by artificial intelligence (AI). Despite record-high revenues for many enterprises, in order to reallocate funds to AI infrastructure and leverage AI to improve operational efficiency, tech giants are intensively restructuring their organizations. Data shows that in May this year, the number of layoffs in the tech industry reached the highest single-month figure in years, with AI as the main trigger for these layoffs.
Specifically, several leading companies have already implemented large-scale workforce reductions. Oracle's latest filing reveals that over the past 12 months, 21,000 employees (about 13% of its workforce) were laid off due to internal AI technology deployments. Amazon cut 16,000 corporate positions in January this year, and management anticipates that widespread adoption of generative AI will significantly reduce the need for traditional roles. Meta, while trimming about 8,000 jobs, reassigned nearly 7,000 employees to core AI business roles. Block executed major layoffs of 4,000 staff, nearly halving its total workforce, in order to adapt to a flatter operational model enabled by AI tools.
In addition, companies including Cisco (4,000 employees), Intuit (3,000), Atlassian (1,600), Cloudflare (1,100), Snap (1,000), an unnamed exchange, Salesforce, and others have also announced substantial AI-driven restructuring and layoff plans this year. Meanwhile, companies such as Google, Microsoft, and IBM have not disclosed specific layoff numbers, but are also continuously pushing forward with rolling job changes and reorganizations tied to their AI strategies.
Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.
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