Meta is cutting thousands of jobs while pouring billions into artificial intelligence programs, raising fears across Silicon Valley that the AI boom could permanently reduce white-collar employment.
The owner of Facebook and Instagram recently cut nearly 10% of its workforce while ramping up spending on AI chips, data centers and supercomputer infrastructure. The layoffs are part of a brutal wave that will hit tech in 2026, with more than 113,000 job openings at 137 companies this year, according to figures cited in a Forbes interview with former Intel CEO Diane Bryant.
For industry insiders, the pattern is becoming impossible to ignore. Companies that once recruited aggressively are now slowing hiring, shrinking teams and redirecting large amounts of money to AI programs.
Time moves workers beyond Meta itself.
Many young tech workers enter the industry believing that software engineering and business technology roles offer almost guaranteed stability, high salaries and constant demand. Now vacancies are spreading, graduate recruitment is slowing and even experienced workers are beginning to question how secure their jobs are in an AI-driven economy.
Bryant, who once led Intel's data center division before becoming Google Cloud's COO, believes a lot of fear is moving faster than reality. He argues that every major technological revolution – from PCs to cloud computing – has created fear long before companies have fully rebuilt themselves around new systems.
But even Bryant admits that this time feels different.
Wall Street is pouring unprecedented sums into AI infrastructure as executives face increasing pressure to prove they can run lean businesses with fewer employees. Companies are increasingly treating salaries as a cost-cutting area as they scramble to fund expensive AI expansions, including Nvidia chips, cloud capacity and massive data center projects.
Inside Silicon Valley, that trade is already changing the way companies hire.
Support departments, custodians and non-profit groups are under a lot of pressure as management looks for ways to cut operating costs. Workers who have survived previous tech downturns now face an entirely new fear: that AI may not only temporarily slow hiring but permanently reduce the number of people companies need.
Bryant said businesses still face major challenges before AI can fully take over large parts of the workforce. Many firms lack the skilled workforce to effectively implement AI systems, while security risks, negative outcomes and employee resistance continue to slow adoption.
He also rejected the growing narrative that AI will replace software development entirely.
Instead, Bryant believes that AI will sit on top of existing software systems rather than directly replace them. Companies will still need engineers, infrastructure specialists and large software platforms as AI changes the way those tools are used.
However, for workers, the disruption is already coming sooner than many expected.
Bryant compared today's concerns to Intel's cloud-computing revolution years ago, when virtualization technology caused panic among longtime infrastructure workers who feared their technology was becoming obsolete. Others are adapting and retraining for new roles. Some disappeared completely from the company.
What makes this AI wave feel so intense is the speed at which money is flowing into it. Big tech firms collectively spend hundreds of billions of dollars to build AI systems as layoffs continue to spread across the board at levels not seen since the post-pandemic tech crash.
For graduates and young workers trying to enter the field now, the situation looks completely different from a few years ago. Competition for jobs has intensifiedhiring pipelines have shrunk and workers are increasingly under pressure to keep training just to stay employable.
Bryant still believes that the AI economy is only in its early stages. But beyond Silicon Valley, many workers are no longer questioning whether AI will reshape the industry.
They wonder how many there are jobs disappear before returning from employment.
