Two jobs can be equally exposed to artificial intelligence yet experience entirely different outcomes, a major new study has shown.
Research by academics at King's College London and the AI Objectives Institute has shed light on why: what matters is not just how much of a job AI can do, but which parts.
Dr Bouke Klein Teeselink and Daniel Carey analysed hundreds of millions of job postings across 39 countries before and after the release of ChatGPT in November 2022. They found that occupations with a large number of tasks exposed to AI automation, for example basic administration or data entry, saw a 6.1 per cent decline in job postings on average. Importantly, however, this effect depends not only on how many tasks are exposed, but also on which tasks.
When AI automates the routine, less-skilled parts of a job, the work that remains tends to be more specialised. Fewer people can do it, so wages rise. The researchers cite the example of a human resources specialist whose administrative paperwork is now handled by AI, leaving them to focus on complex employee relations and judgment calls.
But when AI can perform the more specialised, cognitively demanding tasks, wages decrease because the job no longer requires scarce expertise. This example can apply to roles such as junior software engineers, the researchers found.
The study also found that national context shapes how AI exposure translates into job outcomes. Countries with stricter employment protection laws showed larger reductions in job postings, likely because firms facing uncertainty about whether AI might be able to automate jobs in the future are reluctant to hire workers who may be difficult to let go. Countries with stronger digital infrastructure experienced smaller hiring declines, suggesting that readiness to adopt and adapt to technology might help to reduce displacement.
The researchers argue that effective policy responses to the displacement of workers could not be one-size-fits-all and would need to take account which part of a job AI can automate.
"Workers in occupations where AI may automate high expertise tasks face most acute wage pressures," said Dr Klein Teeselink, a lecturer in economics at King's. "Training programs could target these workers with curricula focused on skills that remain difficult for AI to replicate, particularly those involving judgment, creativity, and interpersonal interaction."
"Conversely, in occupations where AI automates low-expertise tasks, workers can concentrate on higher-value expert work, and policies that encourage AI adoption
in these augmenting contexts may yield productivity gains without displacing labour."
