AI could eliminate half of entry-level white-collar jobs within the next five years. The shift will occur rapidly, with job losses affecting the global workforce sooner than previous waves of technological change.
By 2027, millions of jobs may be displaced or significantly altered. While some roles will evolve, the workforce must prepare for a sharp increase in disrupted employment.
We gathered 15 predictions from AI experts, academic articles, and industry leaders on their perceptions of AI job loss.
AI job loss predictions according to experts
Dario Amodei (Anthropic CEO), 2025
Dario Amodei warned that AI could eliminate 50% of all entry-level white-collar jobs within the next five years, potentially pushing U.S. unemployment rates to 10–20%.
Calling it a possible “white-collar bloodbath,” Amodei emphasized that many CEOs remain unaware of AI’s short-term disruptive power. His message focused on the urgency for lawmakers to act and for AI developers and companies to adopt transparent approaches. He acknowledged that AI continues to offer long-term promise, but stressed that dangerous short-term pain, particularly for junior professionals, must not be ignored.
Entry-level roles involving structured tasks performed routinely by humans are seen as most vulnerable to automation in this scenario.
Kai-Fu Lee (Venture Capitalist), 2025
Kai-Fu Lee echoed Amodei’s concern by validating the projection that AI could displace 50% of jobs by 2027.
As a prominent voice in the field, his agreement adds credibility to the estimate that AI job loss could soon impact half of the global workforce. While his statement is brief, it underscores growing consensus among experts that AI may reshape employment far more aggressively than previous technological change.1
International Monetary Fund (IMF), 2024
The IMF estimated that 300 million full-time jobs globally could be affected by AI-related automation.
However, it emphasized that most will undergo task-level transformation, rather than outright loss. In high-income countries, service-heavy economies make the workforce especially exposed.
The report classified AI’s effects into three categories: automatable (routine, rule-based), augmentable (judgment-driven), and unaffected tasks. Two-thirds of jobs are expected to experience partial automation. It emphasized the complementarity of AI and human labor, particularly in decision-making, pattern recognition, and knowledge retrieval.
The report also highlighted the urgent need for reskilling, projecting that over 40% of workers will require significant upskilling by 2030. Legal, financial, and insurance sectors will undergo the most significant transformation; education and healthcare will remain relatively resistant due to their reliance on human interaction and complex processes.2
Goldman Sachs, 2023
Goldman Sachs forecasted that 300 million jobs worldwide could be lost or degraded due to AI.
The most impacted regions would be the U.S. and Europe, particularly in industries relying on repetitive, structured tasks.
Despite this, Sachs also predicted that artificial intelligence could increase global GDP by 7%, thereby creating new job opportunities and fields. Drawing historical parallels with electric motors and personal computers, the report framed AI as another general-purpose technology, likely to bring both disruption and long-term benefits.
The challenge, however, remains managing this transition without causing deep societal harm, particularly in vulnerable labor segments.3
World Economic Forum (Future of Jobs Report), 2023
The World Economic Forum projected that 83 million jobs would be lost and 69 million created by 2027, amounting to a net loss of 14 million jobs (2% of the global workforce).
Clerical and administrative roles like bank tellers, cashiers, and data entry clerks are most at risk.
On the other hand, roles involving AI development, business intelligence, cybersecurity, and sustainability are expected to grow.
While 60% of companies plan to adopt AI by 2027, only 26% anticipate job growth from it, and half expect job losses. The report also noted that climate transition policies could affect around 10% of jobs, adding a second axis of change alongside technological pressure.4
GPTs and the U.S. Workforce (Eloundou et al.), 2023
A study on the effects of generative AI and large language models concluded that 80% of the U.S. workforce could have at least 10% of their tasks affected.
For around 19% of workers, at least half of their daily tasks could be disrupted.
The most exposed roles include writers, public relations specialists, legal secretaries, mathematicians, and tax preparers, all requiring extensive language or logic-based work.
Unlike past automation, which primarily targeted blue-collar work, LLMs are poised to transform higher-wage, highly educated professions across multiple sectors. Their impact is independent of physical infrastructure, broadening the scale of potential displacement.5
Eric Dahlin (U.S. Survey Study), 2022
A 2021 survey by sociologist Eric Dahlin found that approximately 14% of Americans reported losing their jobs to robots.
Despite this modest actual rate, public perception was significantly inflated: those not affected believed 29% had lost their jobs to automation, while those who were displaced estimated the rate at 47%.
This gap between perception and experience reflects deep anxiety about AI’s impact, even when real-world job loss rates remain lower than often assumed.
The study’s inclusion of robots in non-industrial contexts (airports, libraries, eldercare) further highlighted AI’s reach across different sectors of life and work.
Figure 1: The graph illustrates that respondents significantly overestimated the likelihood of robot-driven job loss, with perceptions ranging from 29% to 47%, compared to the actual rate of approximately 14%.6
World Economic Forum, 2020
In a 2020 report, the WEF predicted that 85 million jobs would be displaced, while 97 million would be created by 2025, suggesting a net gain of 12 million jobs.
However, the report also introduced the idea of “double disruption,” where automation and the pandemic together accelerate job displacement beyond the ability of societies to adapt. It warned that many emerging markets and cities lacked the digital infrastructure or policy agility needed to manage AI’s growing influence on the job market.7
PwC (22nd Annual Global CEO Survey), 2019
PwC’s global CEO survey found that 42% of CEOs believe AI will displace more jobs than it creates, while 39% disagree, reflecting a divided outlook.
Job loss concerns are highest in the Asia-Pacific region, especially in China, where 88% of CEOs expect net job displacement. The report highlights a persistent skills gap, with 55% citing the inability to innovate due to a lack of key skills.
Most CEOs (46%) view retraining and upskilling as the most effective solution. Despite 85% agreeing AI will significantly change business within five years, only 10% have adopted it at scale, hindered by talent shortages and data challenges.8
OECD Study, 2016
An OECD study found that only 9% of UK jobs were at high risk of automation, but that 35% would undergo radical transformation in the next two decades.
This conclusion suggests that fears of mass unemployment may be overstated and that significant changes are more likely to occur through job evolution and reskilling, rather than widespread elimination.9
Bowles (EU Jobs Risk), 2014
Building on Frey and Osborne’s methodology, Bowles estimated that 54% of jobs in the European Union were at risk of computerization.
This emphasized how AI’s impact extends beyond U.S. borders and raised questions about how regional differences in labor protections and education systems might shape the outcomes of technological disruption.10
Frey & Osborne, 2013
In one of the first major academic studies on AI job loss, Frey and Osborne estimated that 47% of U.S. jobs were at risk of computerization. Their research classified occupations based on their susceptibility to machine learning and automation.
This early work helped frame later debates on the future of employment, drawing attention to how tasks rather than entire jobs are automated, prompting nuanced discussions around task restructuring and skills transition.11
Other views on AI job losses
Nvidia CEO Jensen Huang’s view on AI job loss
At VivaTech 2025 in Paris, Nvidia CEO Jensen Huang pushed back against Anthropic CEO Dario Amodei’s warning that AI could replace up to half of entry-level office jobs within five years.
Huang rejected the idea that AI is so dangerous or powerful that only a select few should develop it, instead arguing for open and responsible advancement.
While he acknowledged AI will transform the workplace, making some jobs obsolete, he emphasized that greater productivity typically leads to more hiring, not less, and criticized the fear-driven narrative surrounding AI’s impact on employment.12
“Exponentially bad move”: Dilan Eren (Ivey Business School), 2025
While not focused on percentages, Professor Dilan Eren offered a structural critique of firms that respond to AI by eliminating junior roles. Eren warned that cutting entry-level positions for cost savings is an “exponentially bad move” that threatens the internal talent pipeline.
Without juniors, organizations risk shortages of experienced staff in the coming years, especially as mentorship and on-the-job learning decline. Eren urged firms to develop strategies that support dual development: juniors must build domain expertise, while senior staff must upskill in AI.
Delegating all tasks to machines, Eren argued, risks undermining judgment and weakening collaborative learning within companies.
Positive outlook: Ravi Kumar (Cognizant CEO), 2025
In contrast, Ravi Kumar presented an optimistic vision of AI’s role in employment. He argued that AI will create more job opportunities, especially for recent graduates.
As more companies adopt advanced software, he expects an increase in demand for skilled labor rather than widespread job losses.
According to Kumar, AI can act as a force multiplier, enabling workers to achieve “more for less” while raising expectations, not reducing them. His forecast aligns AI’s rise with productivity, innovation, and new skills acquisition, challenging the notion that AI must necessarily lead to unemployment or widespread displacement.13
Implications of AI on different industries
Most exposed roles and industries
Industries that rely on structured tasks performed routinely by humans face the highest risk. Clerical, legal, finance, and data processing roles are among the most vulnerable.
These jobs are typically easy to automate using AI systems and tools. Tasks that involve predictable patterns or follow fixed rules are most susceptible to errors. Entry-level positions, particularly for young workers, are at high risk of being eliminated.
Uneven impact across sectors
Healthcare and education are less exposed due to the complexity of human interaction required. These sectors are more resistant to automation and large language models.
Partial automation vs. full displacement
Not all job losses will result in full unemployment. In many cases, AI will automate tasks within roles rather than remove entire jobs.
Around two-thirds of current roles are expected to undergo task-level change. Workers will need to adjust to new responsibilities that require human decision-making, reasoning, and creativity. This partial automation still creates pressure on workers to adapt quickly.
Economic and geographic variation
The impact of artificial intelligence will vary by region. High-income economies with service-heavy job markets are more exposed. Emerging markets may face challenges due to limited access to digital infrastructure and fewer resources to reskill the workforce. The difference in local policy responses will influence how AI’s impact unfolds across the world.
What are the perceptions from the actual workers?
Mismatch between perception and reality
Public perception of job losses is higher than the actual reported figures. While real displacement remains below 15% in recent years, workers believe a much larger share of the workforce has already been affected.
This reflects growing anxiety about AI’s impact and the future of employment, despite actual data showing a slower pace of change.
How to leverage AI for workforce advantage?
Importance of reskilling
By 2030, over 40% of workers will need to develop new skills to remain employed. As AI systems continue to evolve, companies must invest in training programs to stay competitive.
Reskilling is especially important for young people entering the job market, where entry-level opportunities are shrinking. Employers must develop strategies that align humans with machines, rather than replacing them entirely.
Organizational risks of cutting junior roles
Firms that eliminate junior roles to reduce costs face long-term risk. Without entry-level staff, organizations lose future talent and weaken internal training structures.
Mentorship and on-the-job learning decline, which impacts decision-making and institutional knowledge. While AI can automate tasks, relying solely on systems creates gaps in workforce development.
Potential for economic growth
Despite widespread concern, artificial intelligence could lead to long-term economic gains. Estimates suggest that AI might boost global GDP by 7%, partly offsetting job losses.
This mirrors past general-purpose technologies that initially displaced workers but eventually created new jobs. However, the challenge lies in managing the short-term disruption without causing unemployment and social instability.
Diverging expectations about the future
Some executives expect artificial intelligence to create more job opportunities. As companies increase adoption, demand may shift toward roles involving AI development, cybersecurity, and sustainability.
These jobs require new skills and align with the growth of AI, which continues to impact how businesses operate. On the other hand, many managers still expect job cuts in the near term, indicating that the outlook remains divided.
External Links
- 1. https://fortune.com/2025/05/28/anthropic-ceo-warning-ai-job-loss/
- 2. https://www.imf.org/en/Publications/Staff-Discussion-Notes/Issues/2024/01/14/Gen-AI-Artificial-Intelligence-and-the-Future-of-Work-542379?cid=bl-com-SDNEA2024001
- 3. https://www.forbes.com/sites/jackkelly/2023/03/31/goldman-sachs-predicts-300-million-jobs-will-be-lost-or-degraded-by-artificial-intelligence/
- 4. https://www.weforum.org/publications/the-future-of-jobs-report-2023/
- 5. https://arxiv.org/pdf/2303.10130
- 6. https://journals.sagepub.com/doi/full/10.1177/23780231221131377
- 7. https://www.weforum.org/stories/2020/10/dont-fear-ai-it-will-lead-to-long-term-job-growth/
- 8. https://www.pwc.com/gx/en/ceo-survey/2019/report/pwc-22nd-annual-global-ceo-survey.pdf
- 9. https://www.oecd.org/en/publications/the-risk-of-automation-for-jobs-in-oecd-countries_5jlz9h56dvq7-en.html
- 10. https://www.bruegel.org/blog-post/chart-week-54-eu-jobs-risk-computerisation
- 11. https://oms-www.files.svdcdn.com/production/downloads/academic/The_Future_of_Employment.pdf
- 12. https://fortune.com/2025/06/11/nvidia-jensen-huang-disagress-anthropic-ceo-dario-amodei-ai-jobs/
- 13. https://www.hrreporter.com/focus-areas/automation-ai/an-exponentially-bad-move-experts-warn-against-cutting-entry-level-jobs-for-ai/392731
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