AI angst mutates into ‘FOBO’ as Fear of Becoming Obsolete takes over American workforces

There’s a new acronym reshaping how workers think about their careers: FOBO — the Fear of Becoming Obsolete. Unlike traditional job insecurity, FOBO isn’t about getting fired. It’s about becoming irrelevant. Four in 10 workers now name AI-driven job loss as one of their primary fears — a share that has nearly doubled in a single year, according to KPMG. Sixty-three percent say AI will make the workplace feel less human. Skill demands in AI-exposed roles are shifting 66% faster than they did just one year ago. In 2026, FOBO became the defining psychological condition of the American workplace.

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After Dario Amodei, CEO of Anthropic, claimed last year that AI could eliminate 50% of entry-level white-collar positions within five years, he was joined within months by Microsoft AI CEO Mustafa Suleyman, who offered a similar outlook. More recently, Senator Mark Warner (D-VA) said that AI leaders themselves have been surprised and alarmed at the pace of disruption, and they are “literally consciously pulling back on their predictions because of the short-term economic disruption.” Warner put the new college grad unemployment at 35% within two years.

These are the predictions feeding FOBO — and they’re landing. A massive new study from MIT wants to pump the brakes. Not on the fear — FOBO, it turns out, is pointing in roughly the right direction — but on the timeline. And the timeline, it turns out, changes everything.

Researchers at MIT FutureTech published findings this week showing that AI’s march through the labor market looks far less like a sudden catastrophe and far more like a slow, rising flood — serious and accelerating, but not the overnight apocalypse that has dominated headlines and executive anxiety for the past two years.

“Rather than arriving in crashing waves that transform a certain set of tasks at a time,” the researchers write, “progress typically resembles a rising tide, with widespread gains across many tasks simultaneously.”

The study, titled “Crashing Waves vs. Rising Tides,” is one of the most comprehensive empirical examinations of AI’s real-world task performance to date. The team of nine researchers led by Matthias Mertens and Neil Thompson collected more than 17,000 evaluations of LLM outputs from domain-expert workers across more than 3,000 labor market tasks drawn from the U.S. Department of Labor’s O*NET classification system. Those tasks spanned everything from legal analysis to food preparation, management to computer science. More than 40 AI models were tested, ranging from GPT-3.5 Turbo to GPT-5, Claude Opus 4.1, Gemini 2.5 Pro, and DeepSeek R1.

For anyone gripped by FOBO, the core question the researchers asked is also the most unsettling one: Can AI complete these tasks well enough that a manager would accept the output without any edits? The answer is already yes — frequently.

Across all models and job categories tested, AI successfully completed roughly 50% to 75% of text-based labor market tasks at a minimally acceptable quality level. That’s not a future projection. That’s today. More specifically, the study found that by the third quarter of 2024, frontier AI models were already hitting a 50% success rate on tasks that take humans about a full workday to complete.

The improvement trajectory is steep. Between the second quarter of 2024 and the third quarter of 2025, frontier models went from clearing a 50% success threshold on 3- to 4-hour tasks to clearing the same bar on tasks that take humans an entire week. Failure rates are halving roughly every two to three years across the board, which translates to annual gains of 15 to 16 percentage points in success rates.

Extrapolating those trends — and the researchers are careful to note this represents an optimistic, upper-bound scenario — AI systems could complete most text-based tasks with 80% to 95% success rates by 2029 at a minimally sufficient quality level. For the majority of survey tasks, which take a few hours for a human to complete, the projected 2029 success rate approaches 90%.

MIT doesn’t use the phrase but this is FOBO, calibrated. The fear isn’t irrational — it’s premature. The water is rising. But the MIT data suggests the floorboards won’t be underwater by next Tuesday. The researchers’ most consequential line for anxious workers: “Workers are likely to have some visibility into these changes, rather than facing discontinuous jumps in AI-driven automation.” The rising tide gives you time to move. The question is whether you’re moving.

FOBO at the institutional level

Here’s the irony: even as MIT documents AI’s sweeping capability gains, most companies have yet to deploy the tools at all. FOBO isn’t just a personal condition, then — it’s an organizational one. According to Goldman Sachs economists Sarah Dong and Joseph Briggs, citing Census Bureau data in their March 2026 AI Adoption Tracker, fewer than 19% of U.S. establishments have adopted AI. Goldman projects that adoption will