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    Home»Technology»Software & Apps»AI was supposed to kill engineering jobs, but new data suggests they’re the most resilient
    Software & Apps

    AI was supposed to kill engineering jobs, but new data suggests they’re the most resilient

    AdminBy AdminJune 24, 2026No Comments4 Mins Read0 Views
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    Whether AI is already replacing jobs is the subject of fierce debate.

    Tech layoffs hit their highest single month total in years in May, and AI was the most-cited reason, according to outplacement firm Challenger, Gray & Christmas.

    Software engineering, in theory, is the professional field most vulnerable to automation, given the rapid adoption of AI-powered coding tools. However, researchers at venture firm SignalFire say the hiring data tells a different story.

    “The rationale given for lots of layoffs is consistently AI, and specifically they’ll say AI with respect to code; they’ll say one engineer could do the job of however many engineers in the past,” said Asher Bantock, SignalFire’s head of research. “What we’re seeing on the ground is a little inconsistent with that.”

    SignalFire’s analysis, which tracked the careers of millions of employees across more than 80 million companies, suggests that engineering was the most resilient job function in 2025. Instead of focusing on layoffs, which are difficult to track because people often delay updating their employment status after job cuts, SignalFire examined hiring data as a more accurate indicator of real-time workforce trends.

    While total hiring across large tech companies dropped 25% compared to 2019 levels, engineering roles saw a much smaller decline of just 11%, according to SignalFire’s latest “State of Talent Report.”

    In fact, engineers comprised 55% of all new hires in 2025 across the 12 companies SignalFire classifies as “Tech Majors” — Alphabet, Meta, Apple, Amazon, Microsoft, Netflix, NVIDIA, Tesla, Uber, Airbnb, Block, and Stripe. This is a significant jump from 2019, when engineers represented only 46% of new recruits, according to the report.

    The continued need for engineers was even more evident at early-stage startups, which collectively brought on 7% more engineers in 2025 than they did in 2019, SignalFire’s data shows.

    If AI were truly substituting for engineering talent, Bantock argued, engineering hiring would be the first to fall amid the current tech hiring contraction. Instead, SignalFire’s data shows that engineering headcount is growing faster than most other job functions in tech.

    While Anthropic CEO Dario Amodei warned last year that AI could wipe out half of all entry-level white-collar jobs and push unemployment as high as 20% within five years, the company’s own head of economics, Peter McCrory, told TechCrunch in March that he had not yet seen any significant AI-driven effects on the workforce.

    Said McCrory at the time: “There’s at least no larger material difference in unemployment rates” between workers who use Claude for the “most central task of their job in automated ways” — like technical writers, data entry clerks, and software engineers — and workers in jobs less exposed to AI that require “physical interaction and dexterity with the real world.” 

    Nvidia CEO Jensen Huang went further still, outright rejecting the theory that AI will replace engineers. “Somebody said that AI is going to destroy all of the software engineering jobs,” Huang said in an interview at the Stanford Graduate School of Business in April. He then argued the opposite is true. Now that all engineers at Nvidia are using agentic AI, “software engineers are busier than ever,” he’d said.

    Huang added that while agents are writing code near instantaneously, they are constantly pushing engineers to generate “the next idea.”

    For now at least, it seems that armed with AI, engineering has become a classic example of the Jevons paradox — the idea that greater efficiency doesn’t reduce demand for a resource; it increases it, because the work expands to fill the new capacity. As Bantock said of engineering talent in this moment: “They’re suddenly a lot more productive, and there’s endless work for them to do.”

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