Andrew Yang Says AI Will Displace Millions Of Workers Within 18 Months

In a commentary circulated this week, Yang predicted that millions of mid-career office workers, call-centre staff, marketers, coders and similar professionals could be displaced by AI within the next 12 to 18 months as generative models and automation tools complete tasks once requiring days of human effort in a matter of minutes. He described the looming shift as a “great disembowelling” of white-collar roles, saying companies that adopt AI to enhance efficiency will put pressure on competitors to do the same, leading to cascading layoffs.

Yang’s estimates are stark: he suggests that 20–50% of the roughly 70 million white-collar workers in the United States might lose their jobs in the coming years as tasks like data analysis, report writing, coding and customer support are automated. He warns these trends could hit consumer spending, housing markets and tax revenues, with broader knock-on economic impacts beyond those directly displaced.

The trend Yang highlights is not unique to him. Other tech leaders and analysts have echoed concerns that AI could rapidly reshape the workforce. Some executives have suggested that AI systems may soon achieve human-level performance on many professional tasks, potentially accelerating the displacement of roles in law, finance, marketing and management.

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Yang and other critics argue that policy responses are needed now to mitigate the social impact. His proposals have included universal basic income, retraining and upskilling programmes, and taxes or regulations on companies deploying AI at scale. These are meant to cushion displaced workers and help economies adjust to structural shifts in labour demand.

Supporters of AI development counter that innovation historically creates new employment opportunities even as it eliminates old ones, and that many jobs will be reshaped rather than fully erased. Nonetheless, the debate reflects a central tension in contemporary economic policy: how to balance technological progress with labour market stability.

The issue has gained renewed urgency as recent corporate layoffs tied to AI strategies and automation trials have fuelled fears that the role of AI in employment will expand rapidly through 2026 and beyond — making adaptation and governance key topics in both private and public sector discussions.

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