TLDR: A recent analysis by IndexBox and JPMorgan warns that generative AI could uniquely destabilize white-collar jobs during future economic recessions. Historically resilient knowledge workers, particularly in non-routine cognitive roles, are now facing increased vulnerability to automation, with data indicating a significant shift in unemployment patterns where these high-skill occupations account for a larger share of jobless individuals than manual roles.
Generative Artificial Intelligence (AI) is poised to fundamentally reshape the labor market, presenting an unprecedented threat to white-collar jobs, especially during periods of economic contraction. A recent analysis, drawing on data from the IndexBox platform and insights from JPMorgan, indicates that businesses are increasingly turning to automation during downturns, potentially placing knowledge workers at a higher risk of layoffs than in previous recessions.
Historically, professions in fields such as science, engineering, and law have shown resilience to economic shocks. However, the accelerating adoption of AI could expose these roles to unforeseen unemployment risks. Data from the IndexBox platform highlights a significant shift: non-routine cognitive occupations, which now constitute nearly 45% of total employment (up from 30% in the 1980s), are for the first time accounting for a larger proportion of unemployed workers compared to non-routine manual jobs. Murat Tasci, a senior U.S. economist at JPMorgan, described this trend as ‘ominous,’ signaling a growing vulnerability for roles requiring analytical or creative tasks.
AI’s impact on the labor market is proving to be uneven. While routine jobs, such as clerical or manufacturing work, have experienced automation-driven declines since the 1980s, AI now threatens to impede post-recession recoveries for high-skill professions. Tasci cautioned that ‘anemic growth’ in these sectors could lead to prolonged jobless recoveries, reminiscent of the struggles faced by routine occupations after the 2008 financial crisis.
Concerns about widespread job displacement are echoed by other industry leaders and studies. Dario Amodei, CEO of leading AI firm Anthropic, has issued stark warnings, predicting that AI could eliminate up to half of all entry-level white-collar jobs within the next one to five years, potentially leading to an unemployment surge of 10% to 20%. Amodei emphasized, ‘Most workers are unaware that this is about to happen.’ He also noted that the shift from AI augmenting jobs to fully automating them could begin ‘in as little as a couple of years or less.’
Evidence of this disruption is already emerging. Swedish fintech company Klarna reportedly reduced its workforce by 38% between 2022 and 2024 by leveraging AI for customer support and financial operations. In India, a 2024 IIM-Ahmedabad study found that 60% of white-collar workers fear job loss due to AI, with 68% believing their roles will be automated within five years. A Business Insider report from June 2025 noted a 19% decline in job postings for AI-doable tasks since ChatGPT’s 2022 debut, with high-exposure roles like database administrators and IT specialists seeing a 31% drop in openings.
The World Economic Forum’s Future of Jobs Report projects a net loss of 14 million jobs by 2027, with 83 million jobs lost and 69 million created due to AI and automation. Goldman Sachs estimates that up to 300 million full-time jobs globally could be affected by generative AI, with a greater impact in developed economies due to their reliance on office work. In the U.S., the report identified that up to 46% of tasks performed by entry-level employees could be automated in the next decade, potentially leading to the disappearance of 10 to 12 million entry-level office jobs.
A Microsoft study, based on 200,000 conversations with its Copilot AI, identified knowledge workers such as writers, historians, CNC tool programmers, brokerage clerks, political scientists, and reporters as being most at risk. Pearson’s Oli Latham, VP of strategy and growth at Pearson Workforce Skills, also stated that white-collar jobs are more likely to be impacted by generative AI than blue-collar roles. McKinsey & Co. estimates that nearly a third of U.S. work hours could be automated by 2030.
The collapse of entry-level jobs has also affected internships and training programs. The National Association of Colleges and Employers reported a 22% drop in internship offers from Fortune 500 companies between 2022 and 2024, with a 34% decline in the tech sector. This decline is directly linked to the increased use of AI in internal processes, as companies find that young workers, once essential for tasks like transcription, data labeling, or content moderation, are becoming less indispensable.
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Despite these dire predictions, some, like tech investor David Sacks, the White House’s AI and crypto czar, offer a more optimistic view. Sacks argues that human oversight of AI tools will preserve jobs, stating, ‘You’re not going to lose your job to AI but to someone who uses AI better than you.’ However, the prevailing sentiment among many economists and AI experts points to a significant and potentially disruptive transformation of the white-collar workforce.
