Former U.S. presidential candidate and founder of the Forward Party, Andrew Yang, has issued a stark warning about the near-term impact of artificial intelligence on white-collar employment, predicting that “millions of white-collar workers” could lose their jobs within the next 12 to 18 months.
Writing on his Substack on Monday, Yang argued that AI-driven workforce reductions could quickly become self-reinforcing across corporate America.
“It will become a competition because the stock market will reward you if you cut headcount and punish you if you don’t,” he wrote, suggesting that once one firm aggressively reduces labor costs through automation, rivals will feel compelled to follow to protect margins and valuations.
He framed the potential shift not as a gradual transition but as a rapid structural reset that could leave mid-career professionals suddenly displaced.
Who Is Most at Risk — and Why?
Yang identified mid-career office workers, middle managers, call center staff, marketers, and coders among those most exposed.
“Do you sit at a desk and look at a computer much of the day? Take this very seriously,” he warned.
The vulnerability of these roles stems from advances in generative AI and autonomous systems capable of handling tasks once considered securely human — drafting reports, writing code, analyzing data, producing marketing copy, responding to customer queries, and even managing workflows.
Unlike earlier waves of automation that primarily targeted manufacturing or routine manual labor, this phase of AI deployment increasingly affects knowledge work. Large language models and enterprise AI platforms are being integrated directly into corporate software stacks, reducing the need for entry-level analysts and potentially compressing middle management layers.
Yang has long warned about automation’s disruptive potential. In a 2018 interview with The New York Times, he predicted that self-driving vehicles could displace truck drivers, a shift he said could “destabilize society” and provoke “riots in the street.” His current forecast extends that thesis to the professional class.
Early Signs: Layoffs and AI as a Corporate Strategy
January recorded the highest number of layoffs for the month since 2009. While much of the reduction has been attributed to economic uncertainty and cost discipline, some companies have explicitly linked restructuring to AI initiatives.
Pinterest said in January it plans to cut 15% of its workforce, describing the move as part of an “AI-forward strategy.”
HP announced in November it would eliminate up to 6,000 jobs by 2028, citing AI initiatives as a driver of operational changes.
At the same time, skeptics argue that some firms may be invoking AI as a convenient narrative to justify broader cost-cutting measures that would have occurred regardless of technological change.
The debate reflects a broader divide among technology leaders. Elon Musk of Tesla and xAI, along with Demis Hassabis of Google DeepMind, have expressed optimism that AI will unlock abundance and productivity gains. By contrast, Dario Amodei of Anthropic has cautioned that significant white-collar displacement may be unavoidable as models improve.
Yang’s argument centers on incentives. Public companies operate under constant shareholder scrutiny. If AI tools enable firms to deliver the same output with fewer employees, equity markets may reward leaner cost structures with higher valuations.
That dynamic could create a feedback loop: early adopters of AI-driven downsizing boost earnings per share; competitors respond to avoid being penalized; workforce reductions accelerate across sectors.
In such a scenario, the timeline compresses. Rather than gradual attrition, companies might implement sweeping reductions once internal pilots demonstrate measurable productivity gains.
Yang also emphasized that the consequences would not be confined to those directly laid off.
“Let’s say you’re a dry cleaner, a dog walker, or a hairstylist,” he wrote.
If office workers stop commuting, demand for business attire cleaning declines, pet services fall as people stay home, and discretionary spending tightens.
This multiplier effect could weaken local service economies built around office districts. Fewer workers commuting daily means reduced demand for transit, food services, retail, and personal care — potentially amplifying the economic contraction beyond corporate balance sheets.
The broader macroeconomic concern is wage compression. “The amount of money getting paid to human labor is about to go down,” Yang wrote, pointing to a potential shift in the distribution of income from labor toward capital.
Structural Transition or Short-Term Alarm?
The scale and speed of AI-induced displacement remain contested. Historically, technological revolutions have eliminated certain jobs while creating others. However, the transition periods have often been uneven and socially disruptive.
Yang has previously championed a universal basic income as a buffer against technological disruption. His latest warning appears designed to underscore the urgency of preparing for a labor market shock he believes is imminent.
For now, the corporate narrative around AI blends opportunity and cost efficiency. But if headcount reductions accelerate in the coming quarters, Yang’s prediction of crowded coffee shops filled with newly displaced office workers may shift from metaphor to visible reality.
