In my most recent post, I highlighted venture capital firm Andreessen Horowitz’s view that white-collar jobs, while not being replaced, will likely be all supplemented or augmented by AI copilots and agents.
A new study suggests professionals and office workers are more vulnerable than more physical jobs to generative AI’s advance, but it is not quite ready to become a job killer across any category. In fact, none of the 2,800 job skills studied were threatened with immediate AI mass extinction.
The study, conducted and published by the Indeed Hiring Lab, employed OpenAI’s GPT-4o model to look at a range of job skills within Indeed’s job postings, from account management to hospitality. In essence, genAI was asked whether genAI could take over certain jobs.
The majority (69%) of skills assessed were “very unlikely” or “unlikely” to be replaced by GenAI. Just over a quarter of skills (29%) could “possibly be replaced by GenAI in the future if businesses change some practices and the tools improve.”
Zero percent of the jobs studied were considered “very likely” to be replaced by AI. “Human work skills won’t be easily replaced in the workforce any time soon,” the study’s authors believe. “Today’s generation of genAI tools are not ‘very likely’ to replace a competent human worker in mastering and performing even a single one of thousands of common work skills identified by Indeed.”
The difference is in how physical a job tends to be. Overall, “as long as a skill requires significant hands-on execution — for example, aviation or cooking skills — the usefulness of genAI will remain limited,” the study’s authors state.
Certain professions — including accounting, marketing/advertising, software development, healthcare administrative support, insurance claims, and recruiting — stand a greater than 50-percent chance of seeing tasks usurped to some degree by AI. For these jobs, “genAI may potentially be able to offer significant knowledge and solve modest problems, emphasizing the importance of continued upskilling and ongoing learning for human workers,” the study’s authors, Annina Hering, Ph.D. and Arcenis Rojas, pointed out.
The catch is, while AI could automate substantial swaths of tasks, it simply may not be up to the task just yet. “Currently, genAI isn’t particularly strong at solving problems using skills found in many common jobs,” Hering and Rojas state.
The occupation most at risk at this point is accounting, where almost 78% of skills “were rated as ‘possible’ or ‘likely’ to be replaced by genAI, and genAI said its problem-solving skills were ‘good’ for 31% of skills common to accounting job postings. But accounting occupations are an outlier — it is the only occupation analyzed in which GenAI said it was at least ‘good’ at problem solving for at least 30% of common skills.”
For most other of the occupations analyzed, “the model’s problem-solving abilities were more limited and the share of skills likely to be replaced by genAI was also lower,” the co-authors state. “If genAI models improve their problem-solving abilities for more skills within more jobs, it’s likely that the share of skills that may eventually be replaced in those jobs will also rise.”
It’s very possible that as AI models progress, they will be taking on more sophisticated problem-solving skills, the study states. “But meaningful changes in digitalization and working norms will need to happen first. The tools can be an immense help for certain time-consuming tasks, such as summarizing dense texts or quickly generating highly polished images or audio. As it stands today, genAI is best suited to applying its skills to help with relatively straightforward work tasks that require only modest problem solving and, most importantly, no hands-on execution.”
