Elyse Betters Picaro / ZDNET
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ZDNET’s key takeaways
- Generative AI could transform jobs more than it replaces them.
- Jobs requiring more physical labor are less exposed to AI automation.
- The rate of AI adoption will vary between industries and businesses.
The rise of generative AI tools in recent years has led to fears of an inevitable jobs apocalypse — a wave of automation akin to the Industrial Revolution that pushes massive quantities of humans out of the workforce.
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At least for the time being, that hasn’t come to pass. Despite predictions from some tech industry leaders that AI will soon replace a significant swathe of human workers, the technology’s impact on the labor market has thus far been minimal.
New data from employment search engine Indeed, however, shows that generative AI is able to automate a growing number of job skills. That suggests that rather than pushing humans out of their jobs entirely, AI will start to become an increasingly important tool within the workplace.
Transformation vs. replacement
Indeed’s latest AI at Work Report, an annual study measuring the technology’s impact in the job market, found that more than a quarter (26%) of jobs that had been posted on the platform in the past year could be “highly” transformed by generative AI.
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The study assessed the capabilities of two models, OpenAI’s GPT-4.1 and Anthropic’s Claude Sonnet 4, and how effectively they were able to perform across a range of close to 3,000 key work skills. To that end, the researchers deployed what they call the GenAI Skill Transformation Index (GSTI), a metric gauging the degree to which generative AI will transform particular job requirements, rather than the technology’s potential to replace jobs wholesale.
“The future of work and the role of generative artificial intelligence (GenAI) is not just about job loss or automation–it’s about transformation,” Indeed noted in the report. “Rather than thinking in either-or terms–jobs lost vs. jobs saved–we must understand GenAI’s impact along a continuum of transformation.”
Which jobs are most exposed?
Each of the job skills included in the new Indeed study were assessed according to their cognitive as well as their physical demands. Jobs that required more of the former, such as software development, were found to be more highly exposed to automation from AI; those that revolve primarily around the latter, including nursing, are less likely to become automated anytime soon, according to the report.
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The findings echo a July paper from Microsoft, which similarly found that roles requiring the kind of repetitive information-processing at which large language models excel, like translation and customer service, were more likely to be replaced by the technology.
Only 19 skills in Indeed’s new study (0.7% of the total dataset) were deemed “very likely” to be fully replaced by generative AI. This is up from zero in the company’s previous studies, however — “still small in absolute terms,” the authors note in the report, “but a significant signal of progress.”
Another recent study analyzing online job postings from the past 13 years found that jobs that require more AI-related skills are offering higher salaries than those that don’t, both within the tech industry and across other sectors.
Takeaway for businesses
Just as AI-powered automation could turn out to take place on a continuum rather than on an either-or basis, not all employers are adopting AI at an equal pace. The rate of automation even within those sectors that are most amenable to having some key skills replaced by AI will vary depending on how aggressively individual businesses deploy the technology.
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As Indeed’s report suggests, generative AI isn’t a one-size-fits all solution. AI developers may be making grand promises of boosted employee productivity across the board, but the technology’s utility within individual businesses and roles depends on a wide variety of factors.
Successfull AI adoption will require a fair bit of experimentation on the part of individual businesses. As Indeed noted, for example: “For businesses seeking to more broadly implement GenAI into their workflows and products, choosing the right model for their specific processes and business cases will be critical in ensuring reliable insights.” Recent reporting from authorities like Gartner emphasize that view.
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Rather than enforcing a top-down approach to implementing generative AI throughout the workplace, it could very well turn out to be much more effective to give individual employees the freedom and flexibility to start using the technology in a manner that’s best-suited to their particular roles. This was one of the key findings from a recent MIT study, which found that around 95% of generative AI initiatives among businesses have completely fallen flat.
