When Gbenga Ajilore reflects upon the current state of America’s employment landscape, a series of pressing economic issues occupies his mind, often leaving him restless long after working hours. Chief among these concerns are the waning appetite for entry-level workers, the unpredictable web of tariff-related disruptions, and the suffocating pressure created by persistently high interest rates. By contrast, the ongoing conversation surrounding artificial intelligence and the supposed dangers it poses to the labor force does not trouble him. To Ajilore, who serves as the chief economist at the progressive-leaning Center for Budget and Policy Priorities, AI represents an innovation that will eventually permeate every aspect of professional and personal life, but that moment has not yet arrived. As he puts it candidly, the economy feels paralyzed—stalled by forces much older and broader than the sudden rise of digital assistants.
Indicators from across the U.S. labor market support Ajilore’s apprehension. Unemployment trends, particularly in long-term metrics, are slowly but sharply rising. The number of Americans actively searching for meaningful work has surpassed the number of open positions waiting to be filled. The headlines chronicling layoffs ring almost daily, and the nation’s unemployment rate has climbed to 4.6%, exceeding forecasts. For young workers attempting to gain a foothold, entry into established career paths feels increasingly unattainable, while seasoned employees in their fifties and sixties hesitate to retire, conscious that uncertainty shadows their savings. Simultaneously, corporate hierarchies have flattened dramatically, eroding the once solid mid-tier “rungs” of professional advancement. Only a handful of sectors—healthcare and construction most notably—continue to expand. This creeping stagnation has been dubbed a “white-collar recession,” a disheartening development for Americans who once assumed that higher education was their ticket to stable, well-compensated employment.
Given the turbulence, it is tempting to direct collective frustration at artificial intelligence. Corporate executives across industries have publicly endorsed their all-in commitment to AI-driven strategy, a rallying cry that has left employees anxious about their own relevance. The technology has already begun to redefine how worker performance is assessed and how employers measure output, eroding the boundaries between human ingenuity and machine precision. In hiring, AI’s algorithms have flooded human-resources pipelines, overwhelming departments with automated applications. Many prospective candidates now describe sending out hundreds of resumes—each one seemingly disappearing into the digital void. This has fueled a spirited debate among economists and investors alike: Is AI the inevitable cornerstone of tomorrow’s workforce, or merely a short-lived speculative bubble inflated by hype?
The truth, as Ajilore and others argue, is less glamorous but far more consequential. Artificial intelligence has become an easy scapegoat, a convenient face for the deeper malaise afflicting the economy. Beneath the surface lies a harsher reality: years of increasingly tight monetary policy, resilient inflation, and muted wage growth have fostered a chilling environment in which both small businesses and major corporations trim expenses to survive. As borrowing costs climb, the middle class bears the brunt, stretching each paycheck simply to maintain status quo. If you are disappointed by your stagnant raise or struggling to find a new role, Ajilore suggests that the fault lies not with automation but with the architects of fiscal restraint—most prominently, Federal Reserve Chair Jerome Powell.
The anxiety surrounding AI’s employment impact has found its most iconic visual in what commentators have dubbed “The Scariest Chart in the World.” Widely circulated on social platforms like X and Bluesky and dissected in financial newsletters, this deceptively simple two-line graph juxtaposes two data series: the S&P 500’s performance and the total number of U.S. job vacancies since 2015. For several years, the lines march upward together in perfect harmony until 2022, when they dramatically diverge. The stock market continues to soar while unfilled positions decline. To AI skeptics, this split coincides ominously with the public introduction of ChatGPT, suggesting that large language models instantly began erasing thousands of jobs even as corporate profits skyrocketed.
It is undeniable that AI-based tools have made employees faster and more efficient, capable of composing emails, writing code, and automating repetitive tasks. Such gains should, at least theoretically, make companies more lucrative—and lead to reduced staffing needs. Supporting anecdotes do abound: Nvidia encourages staff to deploy AI “for every task possible,” Microsoft has publicly described its intention to reimagine its entire business model, and law firms and banks increasingly rely on AI-assisted drafting, analysis, and data management. Yet, despite these examples, Ajilore argues that the narrative of immediate AI-driven job loss is “overblown.” In reality, many organizations treat AI as a shortcut—a “cheat code,” he says—rather than a carefully integrated productivity enhancer. Such reliance can actually introduce inefficiencies as companies cut corners and misapply untested tools. Even Federal Reserve Chair Powell, the world’s most influential economic policymaker, maintains that AI is but one small piece of a much larger tapestry driving employment trends today.
Crucially, nearly every discussion of the supposed AI-job-market collapse omits one essential factor: the federal funds rate. Determined eight times a year by Powell and the Federal Open Market Committee, this benchmark interest rate governs the cost of borrowing across the economy. When rates are low, loans for businesses and consumers alike become relatively affordable, spurring expansion, hiring, and consumer spending. When rates rise, the price of credit increases, slowing growth but cooling inflation. Businesses operating under higher financing costs inevitably scale back, and payrolls often become the first casualty.
The correlation between ChatGPT’s launch and the downturn in job openings is therefore coincidental but not causal. From early 2022 through late 2024, the Fed aggressively raised rates by more than five percentage points, ending over a decade of the near-zero-rate environment that had persisted since the 2008 financial crisis. The change reshaped corporate behavior: easy capital evaporated, debt financing became burdensome, and firms redirected focus from expansion to austerity. The Federal Reserve’s own Beige Book—a qualitative report built from interviews with business owners nationwide—captures this shift vividly. Earlier editions in 2021 chronicled “robust demand” for workers and “modest to strong” hiring momentum. By late 2022, the tone had shifted sharply: “Interest rates and inflation continued to weigh on activity,” one entry recorded, while another noted a broad weakening of labor demand in technology, finance, and real estate. The effects rippled through every layer of employment, from entry-level factory positions to high-paying corporate roles.
As the corporate sector adjusted to this new financial climate, a narrative of “efficiency” emerged. Executives across the board—particularly at giants like Meta, Amazon, Google, and Microsoft—publicly reframed layoffs not as reactive cost-cutting but as forward-thinking optimization. The message to investors was simple: fewer employees, more profit. The Beige Book’s subsequent volumes from 2023 onward reinforced this observation, noting a clear pattern of companies reducing their hiring plans and tightening budgets in response to rising borrowing costs. Although some hiring declines were linked to AI’s incremental integration in call centers or accounting departments, the data overwhelmingly blamed macroeconomic uncertainty, tariffs, and high rates rather than automation itself.
Nevertheless, attributing layoffs to a dull economic mechanism such as the cost of credit seldom excites anyone. AI, in contrast, provides a dramatic and future-focused explanation that also helps reassure investors that today’s cuts are tomorrow’s efficiency gains. Chen Zhao, Redfin’s head of economic research, observed that many firms, especially in real estate and technology, face a strained balance sheet where borrowing expenses have skyrocketed. Publicly, they couch these struggles in the language of innovation—emphasizing AI productivity—because “it sounds a lot better to investors,” she remarked, than admitting financial tightening is forcing retrenchment.
History offers perspective. Every transformative technology before AI—from the personal computer to the smartphone, from the internet to industrial robotics—has altered labor markets in waves rather than earthquakes. Economists broadly agree that AI’s long-term impact will unfold gradually over many years, if not decades. Indeed, while certain functions will undoubtedly vanish, entirely new categories of employment are likely to emerge alongside them. As Scott Lincicome of the Cato Institute notes, the trajectory of technological evolution is typically slower than either its enthusiasts or its detractors predict. AI’s present capabilities, he says, are still far from replicating human judgment, ethical reasoning, and creativity. Disruption is inevitable, but apocalypse is not.
Today’s job market appears caught in an uncomfortable limbo. Despite worsening indicators, the Fed has cautiously trimmed rates only three times this year, reflecting a balancing act between safeguarding economic stability and containing stubborn inflation. Internal divisions within the central bank deepen as policymakers debate how fast to act, with projections suggesting slower easing than once expected. Borrowers may eventually find relief, but businesses continue to face a landscape defined by costly financing and constant policy shifts. The added complication of volatile tariffs discourages investment, and reduced immigration has also begun to limit overall labor participation, compounding structural constraints.
When Ajilore surveys these developments, his concern is not about robots replacing human beings, but rather about workers being priced out of opportunity by financial forces beyond their control. The anxiety pervading America’s workforce is therefore understandable: high rates, global trade instability, and cost-cutting corporate habits have collectively stalled forward momentum. Over time, the economy will adapt, just as it has with every previous technological revolution. For now, however, the true antagonist in this story is not artificial intelligence but monetary policy itself—the federal funds rate, quietly setting the tempo for the entire nation’s employment symphony.
Sourse: https://www.businessinsider.com/forget-ai-heres-the-real-reason-the-job-market-sucks-2025-12
