AI’s job winners vs losers: Study exposes shocking divide

Forget the old joke about a coding degree leading to unemployment — now data science backs it up.

A new Stanford Digital Economy Lab study reveals young workers (ages 22-25) in AI-exposed fields like software engineering and customer service have seen a 13% drop in employment since late 2022, even as overall jobs grow.

The study’s biggest takeaway?

AI is hitting early-career workers hard, serving as “canaries in the coal mine” for the broader labour market shifts ahead.

Co-author Erik Brynjolfsson says, “It was really striking to see such a sharp effect for certain categories and not others.”

Older workers in these same fields aren’t feeling the pinch — in fact, employment for workers over 30 in high AI-exposure jobs has grown between 6-12%, likely due to experience and organisational standing.

Where jobs are stable

Meanwhile, jobs in hands-on areas like healthcare aides and taxi drivers have remained stable or increased.

The data rules out other causes like COVID or education shifts, strongly suggesting AI automation is reshaping who gets hired.

“Our findings are consistent with the hypothesis that AI is having this effect,” says co-author Bharat Chandar told TIME.

Where AI-related jobs are growing

Interestingly, jobs where AI augments rather than replaces work — helping humans learn or validate output — show employment growth, highlighting a future where humans and AI collaborate.

Brynjolfsson sums it up: “If we want to create not just higher productivity, but widely shared prosperity, using AI to augment and not just automate work is a good direction to go.”

The researchers even used AI to help analyse the data and write the paper, calling it an “augmentative use.”

So, who’s losing jobs to AI?

The sharp answer: Early-career workers in "AI-automatable" roles, especially in tech and customer service.

But the silver lining is that smart AI use could create new opportunities — if we steer it right.

AI, the authors pointed out, is both the disruptor and the tool to understand its impact.

This study shines a light on the tricky AI-labour landscape ahead — where innovation brings disruption and opportunity in equal measure.