BofA throws cold water on AI apocalypse panic: 60% of today’s jobs didn’t exist in 1940

The doomsday crowd may want to check its history books.

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As fears of an AI-driven jobs apocalypse intensify across boardrooms, union halls, and college campuses, Bank of America’s global research team is urging a reality check. In a report published April 28, BofA economists argue that the “Armageddon narrative” around artificial intelligence “sits uneasily with both economic theory and the evidence so far”—and they’ve got 85 years of labor market data to back them up.

The bank’s central argument is simple: 60% of the jobs that exist in the United States today didn’t exist in 1940. Data scientists, social media managers, and cloud developers “barely existed 20 years ago but are now mainstream jobs.” Agriculture, which employed roughly 40% of Americans in the early 1900s, now accounts for just 1% of U.S. employment.

In each case of transformation—the Industrial Revolution, electrification, computerization—the economy didn’t just survive the disruption. It invented its way out of it.

“Adaptability is the new job security,” the report concludes.

One in four jobs at risk

The bank isn’t sugarcoating AI’s reach. Globally, roughly 840 million jobs, about one in four, are exposed to generative AI, with high-income economies facing the steepest exposure at 33% of all jobs. Younger workers, women, and the highly educated face the greatest disruption risk, largely because they’re concentrated in the white-collar, language-intensive, and administrative roles that AI can most readily assist or automate.

But BofA drew a sharp distinction between exposure and elimination. According to International Labor Organization data cited in the report, 13% of global jobs sit in the “augmentation” category—meaning AI will enhance, not replace, those workers—versus just 2.3% with genuine automation potential.

“GenAI will primarily augment rather than replace workers,” the bank writes, with professional and financial services standing to benefit most and repetitive roles in customer service, information/communications technology, and administration facing the highest substitution risk.

The ATM argument—and its limits

BofA leans heavily on a favorite economist’s parable: the ATM. When automated teller machines proliferated in the 1970s and ’80s, conventional wisdom held that bank tellers were finished. Instead, lower operating costs allowed banks to open more branches, and tellers were redeployed into sales and customer service. The result was increased total teller employment.

Similarly, word processors didn’t eliminate clerical workers; they shifted them toward coordination and communication roles. Excel didn’t gut accounting departments; it expanded them. E-commerce didn’t kill retail employment either; the U.S. still has roughly 15 million to 16 million retail workers today, about the same as in the 1990s.

But the ATM parable cuts both ways. Economist and essayist David Oks argued in an influential, widely read Substack post that most of this ATM story is just half the tale. Since the early 2000s, when you could upload checks onto your iPhone and Venmo your friends for meals, “bank teller employment has fallen off a cliff.”

“It is paradigm replacement, not task automation, that actually displaces workers,” Oks wrote. The worry, then, is not that AI will slot into existing workflows and do them a bit faster. It’s that agentic AI—systems that can autonomously execute multistep tasks, rewrite codebases, orchestrate entire workflows—may not automate the job. It may make the job irrelevant.

BofA acknowledged the risk, flagging agentic AI as a “more structurally disruptive force” that shifts AI from a task-level assistant to, in the bank’s own framing, “AI as worker itself.”

The Jevons paradox

Then there’s the Jevons paradox. Writing in the 1860s, economist William Stanley Jevons observed that making steam engines more fuel-efficient didn’t reduce coal consumption—it caused coal consumption to explode, because cheaper energy unlocked entirely new industrial demand.

Apollo Global Management chief economist Torsten Slok has been increasingly applying the same logic to AI, dubbing it the “Jevons employment effect.” As AI makes professional work cheaper, the total market for that work tends to expand rather than contract, potentially growing headcount in fields from law to accounting to consulting.

The open question for AI is whether cheaper legal memos and financial models will unlock new, previously unmet demand or whether most of that was already being served with AI simply doing the same work with fewer people. Oks’s iPhone counterpoint applies here too: Jevons worked for the ATM but hasn’t worked for the bank teller.

Wall Street optimists in good company

BofA’s research team isn’t alone in reaching for history as a rebuttal to panic. Fundstrat’s Tom Lee has made a similar argument using flash-frozen food.

In the 1920s, Clarence Birdseye’s invention of commercial flash freezing reduced farm labor fr