As the labor market experiences a cooling trend, securing jobs has become increasingly challenging, particularly for young workers. Recently, artificial intelligence tools have been scrutinized as a potential reason behind this challenge.
However, a recent study conducted by Yale University’s Budget Lab in collaboration with the Brookings Institution indicates that attributing the hiring slowdown to AI is premature. The underlying shifts within the workforce actually began before the widespread adoption of ChatGPT.
“While AI may significantly impact labor markets in the future,” states Martha Gimbel, executive director of The Budget Lab and co-author of the study, “there is currently no evidence that it has had any macro-level impact.”
This study delves into how significant technological advancements have influenced the occupational mix of the workforce. Essentially, it examines how the job composition in the U.S. economy evolved following the advent of computers in 1984, the internet in 1996, and ChatGPT in 2022.
Both computers and the internet have undeniably transformed the workforce over the past several decades. Now, generative AI is on track to create similar changes. Nevertheless, analyzing the 33-month mark—approximately the time ChatGPT has been broadly accessible—shows that the impact of AI thus far resembles that of previous technological advancements and mirrors the 2016 benchmark period, which was unrelated to any technological breakthroughs.
“Changes in the occupational mix were already underway in 2021, prior to the emergence of generative AI,” the report notes, emphasizing that “recent changes do not appear any more pronounced,” even with the surge in AI popularity.
Nonetheless, this study arrives at a time filled with anecdotes and ambitious forecasts claiming that AI is fundamentally reshaping the workforce—particularly affecting recent college graduates.
For example, in May, the economic research firm Oxford Economics reported that “there are indications that entry-level positions are increasingly being displaced by artificial intelligence.” More recently, Walmart CEO Doug McMillon made bold assertions regarding AI at a workforce summit in September.
“It’s abundantly clear that AI is going to transform virtually every job,” he stated.
While the study from the Budget Lab and Brookings refrains from forecasting the future, it clearly indicates that AI’s influence on the overall job market has been nearly imperceptible thus far.
At least, for the time being.
“Historically, even the most disruptive technologies take time to exert a large-scale impact on workers,” says Molly Kinder, a fellow at Brookings and another co-author of the study. “Currently, it appears to resemble an evolution rather than an overnight revolution in jobs.”
What Factors Are Influencing Job Availability Besides AI?
While it may be premature to directly blame AI for hiring challenges, the labor market is undeniably undergoing a significant transition.
“In my view, a more plausible explanation for the current softness in new grad hiring is the overall sluggishness of the job market,” asserts Daniel Zhao, chief economist at Glassdoor, who was not part of the study.
On one hand, the unemployment rate stood at 4.3% as of August, which is historically considered low. (Due to the ongoing government shutdown, the Labor Department did not release September figures.)
Conversely, interest rates have remained at 4% or higher for nearly three years, following a period of hovering just above 0% after the Great Recession. Elevated interest rates are primarily employed to control inflation, but they also tend to decelerate the labor market as businesses allocate a larger portion of their budgets toward interest payments rather than staffing.
When the job market experiences difficulties, economists frequently regard young workers as the canaries in the coal mine, as the impact tends to manifest sooner and more visibly for them than for those with established careers.
At present, young workers and recent college graduates are facing significant challenges.
“Our economy has witnessed a marked slowdown in hiring,” states Gimbel. “Current hiring patterns resemble those seen in 2011, which is concerning for young workers.”
As of June, the unemployment rate for young workers was 7%, while for recent college graduates, it was 4.8%, based on the latest figures from the New York Federal Reserve. At that time, the unemployment rate for individuals across all education levels was 4%.
Historically, recent college graduates have enjoyed lower unemployment rates than the overall population; however, that trend has shifted. While AI is frequently blamed for the unusually high unemployment rates among recent graduates, experts suggest that other factors are likely at play.
Is There an Oversupply of Graduates in the Job Market?
One significant contributing factor is the increasing number of college graduates entering the workforce.
According to the St. Louis Fed, nearly 40% of the workforce now holds a bachelor’s degree or higher, a sharp increase from around a quarter of all workers in the early 2000s. As of 2021, only 22% of jobs required a bachelor’s degree, while 36% required a four-year degree or higher.
Regardless of the influence of AI, an oversupply of graduates compared to the number of jobs that require such qualifications results in higher unemployment and underemployment rates within this demographic. This is simply a matter of mathematics.
A Money analysis of data from the New York Fed reveals that recent college graduates enjoyed lower unemployment rates (and often significantly lower) than the overall workforce from 1996, the earliest year on record. However, this trend reversed in 2018.
Since then, it has become the norm for recent graduates to face consistently higher unemployment rates than the general population. Simultaneously, the proportion of the workforce possessing a bachelor’s degree has continued to rise. Both trends began years before the widespread public adoption of AI.
“The demographic of college graduates today differs significantly from that of two decades ago,” Gimbel explains, “and consequently, we should anticipate differing labor market outcomes.”
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