Certain white-collar jobs are heavily over-represented in the Gemini usage data.
Certain white-collar jobs are heavily over-represented in the Gemini usage data. Credit: Google Research
The researchers also attempted to measure how deeply AI was being integrated into various jobs, looking at how often individual, granular O*NET work tasks were attempted using Gemini. Across that entire database, the ATLAS researchers only classified 21 percent of all work-related tasks as “Gemini tasks”—those that met a minimum threshold of 25 related interactions attempted in the massive sample.
For many occupations (29%), not a single relevant work task achieved this “non-negligible” Gemini usage threshold, suggesting those jobs have been minimally impacted by the AI revolution so far. For another 30 percent of all occupations, less than one-quarter of tracked tasks saw significant related Gemini usage, suggesting humans were still the ones responsible for the vast majority of the component parts of those jobs.
In only 3 percent of occupations was Gemini being regularly consulted for at least three-quarters of that job’s relevant tasks. Jobs like software quality assurance analysts and testers, human resources specialists, and document management specialists fell into this bucket and are seemingly the most impacted by AI use in the study.
For the majority of jobs, less than 25 percent of O*NET tasks saw significant attempted assistance from Gemini.
For the majority of jobs, less than 25 percent of O*NET tasks saw significant attempted assistance from Gemini. Credit: Google Research
Altogether, the researchers write, these kinds of numbers suggest that “AI is currently serving primarily as a complement to existing work” and that “AI appears useful for a subset of tasks performed within occupations, but they do not currently appear to be comprehensively used for performing the work currently done by humans.” While the researchers say that this state of affairs may change “as new AI breakthroughs emerge,” it’s also possible that new workflows “will maintain a degree of complementarity between workers and AI systems.”
Give AI the low-expertise, non-routine work
Beyond looking at high-level occupations, the Google researchers also looked at the specific kinds of work tasks that Gemini users ask the model to undertake. Cognitive tasks (i.e. those that primarily involve thinking) represented a whopping 86 percent of the Gemini interactions measured (by volume), while interpersonal and manual tasks were underrepresented in the sample compared to their workplace prevalence.
