AI isn't killing jobs, it's 'unbundling' them into lower-paid chunks
Paper argues the real impact isn't job loss but narrowing human work and pay
AI isn't killing jobs wholesale – it's quietly chipping away at them, one task at a time.
That's the gist of a new research paper making the rounds, which pushes back on the idea that more AI exposure automatically means fewer jobs. The authors argue the real question isn't how many tasks a model can do, but whether those tasks can actually be split out without breaking the role.
Analysts have long warned that automation could wipe out millions of jobs. One recent forecast put the number at 10.4 million US jobs gone by 2030, roughly 6 percent of the workforce. The implicit assumption behind those numbers is straightforward: if AI can do enough of what you do, you're toast.
This new paper – written by Luis Garicano, professor at the London School of Economics, along with Jin Li and Yanhui Wu, both at the University of Hong Kong – suggests it's not that simple.
Jobs, it argues, aren't neat lists of tasks – they're bundles. Radiologists, for example, don't just read scans. They interpret edge cases, talk to clinicians, and sign off on decisions people act on. Replace the image-reading bit, and you haven't necessarily replaced the job.
That's where the authors draw the line between what they call "weak bundles" and "strong bundles." Weak ones can be split apart without much fuss, but strong ones can't without losing value.
"In weak-bundle occupations, AI automates some tasks and narrows the boundary of the job… In strong-bundle occupations… AI improves performance inside the job, but does not remove the human from the bundle," the authors argue.
In weak-bundle jobs – think churning through support tickets or knocking out predictable bits of code – AI doesn't just replace a task; it reshapes the job. The human is left doing whatever the machine can't, often a narrower slice of the original role.
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Sounds like a win on paper. In reality, not so much.
Once AI takes over part of the work, the human stops dividing their time. They go all-in on what remains, which means output per worker jumps, prices fall, and suddenly you don't need as many workers as before.
In other words, the hit to employment doesn't come from AI doing the job outright, but from humans becoming too efficient at the leftovers.
It also squares with what we're seeing so far. AI is reshaping jobs, not wiping them out. Tasks move around, productivity may go up, yet employment and hours haven't shifted much – at least yet. In many cases, the bundle is still holding.
It also explains why the doom predictions and the techno-optimism can both be right at the same time. If you're in a strong-bundle job – something heavy on judgment, context, or responsibility – AI is more likely to make you faster and better paid. If you're in a weak one, it may quietly hollow out your role until there's not much left to defend. ®
