“Artificial intelligence is going to replace literally half of all white-collar workers in the U.S.”- Jim Farley, CEO of Ford Motor Company

Claims like this have been repeated so often that they have helped turn US public opinion against AI in numerous polls:

• 67% of Americans believe that AI will eliminate more jobs than it creates (September 2025 Marist poll).
• 70% think that artificial intelligence will lead to fewer job opportunities (March 2026 Quinnipiac poll). This is a substantial increase from the preceding year, when a similar Quinnipiac study put the figure at 56%.
• 79% believe AI will reduce jobs over the next decade (May 2026 survey of 3,270 US adults conducted by the Gallup organization).

But experts point out that while AI will indeed eliminate some jobs, it will also create new ones.  According to the Future of Jobs Report 2025 from the World Economic Forum “By 2030, 170 million new jobs will be created… while 92 million jobs are displaced, resulting in a net increase of 78 million jobs.”  They based this conclusion on a survey of C-level executives at 1,043 large companies in 55 economies that account for 88% of global GDP.

It is important to emphasize that these particular figures are based not just on AI but also on other new technologies. But unlike many surveys, this report looked at both sides of the coin: not just how many jobs are eliminated, but also how many new jobs are created. 

Predicting the future is never easy, and predicting the societal impact of a rapidly changing technology like AI is particularly difficult.  For example, in 2016 the “Godfather of AI,” Nobel prize winning cognitive scientist Geoffrey Hinton, made this prediction at a conference:  “I think if you work as a radiologist, you’re like the coyote that’s already over the edge of the cliff but hasn’t yet looked down, so doesn’t know there’s no ground underneath him. People should stop training radiologists now. It’s just completely obvious that within 5 years, deep learning is going to do better than radiologists, because it’s going to be able to get a lot more experience.”  

But the reality today is that “Nearly ten years later, radiology is one of the highest-demand, best-paid specialties in the U.S…. of the more than one thousand FDA-cleared AI devices for radiology, not one is authorized to diagnose autonomously without a radiologist’s sign-off.”

To cut through all the noise, last June the Wall Street Journal conducted a panel discussion subtitled “how 16 top economists think AI will change the job market, and how to prepare.”  In a shocking turn of events, the economists disagreed with each other.  For example, when they were asked “Will AI adoption significantly reduce or expand demand for white-collar jobs?” five said AI would reduce white collar jobs, three said expand jobs, six predicted no change, and three refused to venture an opinion on this question.

One of the many reasons they disagreed is that it is hard to say exactly when AI led to layoffs and when other factors were partially or entirely responsible.  This has become such a common problem that analysts invented the phrase “AI washing” to refer to CEO announcements of large layoffs that could have actually been caused by economic conditions and mismanagement.

For example, last April “financial technology company Block announced… that it was laying off 40 percent of its staff, around 4,000 people, because of the progress it claims to be seeing with AI.”  But some former Block employees “contend that poor management left Block with a bloated payroll and that AI is just a convenient excuse for the pink slips.”

As Dean W. Ball, one of the participants on the WSJ panel, put it “I don’t know what the unemployment rate will be in 2028, but I guarantee you that 100 percent of it is going to be blamed on AI by the American public and by lots of opportunistic politicians.”

Historical reactions to other technological advances have often involved prophecies of doom.  For example, according to research conducted by James Bessen, when ATMs proliferated in the 1990s, some experts predicted massive teller layoffs.  ATMs did have the effect of reducing the number of tellers per branch (from about 21 to 13).  But the total number of U.S. bank teller jobs kept growing after 2000 — faster than the labor force overall — because cheaper branches meant banks opened more of them, and tellers shifted into relationship/sales roles.

Similarly, according to a 2026 opinion piece in the New York Times entitled Why the AI Job Apocalypse (Probably) Won’t Happen, “in the early 1980s… around 16.5 million Americans worked in office operations and administrative support. Despite all the information technology inventions that have automated such secretarial tasks as taking dictation and making copies, almost the same number of Americans work in this sector today. They just do different things.”

When the first electronic spreadsheet (VisiCalc) was introduced, “There were predictions of mass unemployment for bookkeepers. Instead, the number of accountants quadrupled over the next 40 years.”  Overall, according to a McKinsey report titled Internet Matters, 2.6 jobs were created for every 1 job destroyed by the internet.

Marc Andreessen, the co-founder of Netscape has noted that: “Even though every new major technology has led to more jobs at higher wages throughout history, each wave of this panic is accompanied by claims that ‘this time is different’ – this is the time it will finally happen, this is the technology that will finally deliver the hammer blow to human labor. And yet, it never happens.”

For AI, in the short term, as a recent Foreign Affairs article put it: “the relative speed and scale of initial job destruction [is] likely to exceed the speed and scale of job creation.”  But in the long-term AI will increase the total number of jobs.  In the Wall Street Journal panel the only question all economists agreed on was that AI will “meaningfully bolster labor productivity.”

To fully realize this potential, according to Sulaekha Kolloru, Chief Strategy Officer at Pearson “sustained productivity benefits will come through people’s ability to harness the technology effectively. This will only be achieved by addressing the ‘learning gap’ between what AI tools can do and how well workforces can use them. The most successful organizations will invest in building the human capabilities that are essential for success – such as critical thinking, creativity, and discernment – alongside AI fluency.”

This long-term optimism is comforting to those who can afford to focus on the big picture, but it will be little consolation to people who lose their jobs in the short-term.

Given the ever-expanding capabilities and scope of AI, which jobs are most likely to be eliminated in the short-term?  Prediction is difficult because, as one expert interviewed for a recent New York Times magazine article put it: “I don’t think we can predict well enough to say, [for example] go be a plumber, because then the Plumbot10000 could come out in a couple of weeks.”

This has not stopped others from trying to predict.  In the last two years, several large surveys have used different methods to make these predictions, and they have come up with slightly different lists. The Pew Research Center published this list of the occupations “most exposed to AI” based on a survey of 5,273 U.S. adults:  “budget analysts, data entry keyers, judicial law clerks, web developers, mechanical drafters — largely white-collar, computer-based, higher-education-credentialed roles.”

The World Economic Forum’s “Future of Jobs Report” surveyed over a thousand C-level executives to come up with their list of the occupations most likely to decline by 2030:  cashiers and ticket clerks, administrative assistants and executive secretaries, printing and related trades workers, bookkeeping and payroll clerks, and material-recording and stock-keeping clerks.

Microsoft Research took a very different approach to the topic by analyzing 200,000 anonymous conversations in Bing Copilot to see which occupations had the most frequent discussions about AI impacting their jobs.  Their list of the occupations “most exposed to AI” began with: interpreters and translators, historians, flight attendants, sales representatives, and writers. 

More important than the exact list of occupations is the question of who is most at risk within each profession.  According to Foreign Affairs, AI is “predominantly affecting the young rather than the old, the more educated rather than the less educated, and the full sweep of industries rather than mainly manufacturing.”

When the Stanford Digital Economy Lab looked for evidence of AI’s impact on youth, they reviewed millions of payroll records from tens of thousands of companies.  They focused on  trends between the time ChatGPT was released in 2022 and July 2025.  “The researchers found that workers between the ages of 22 and 25 in the occupations most exposed to AI, such as software developers and customer service representatives, experienced a six percent decline in employment. ‘In contrast, employment trends for more-experienced workers in the same occupations… have remained stable or continued to grow.’”   

This lack of entry level jobs could have a significant impact on the entire generation unlucky enough to now be in their twenties.