What jobs are affected by AI? Better-paid, better-educated workers face the most exposure

White-collar jobs (better-paid professionals with bachelor’s degrees) along with production workers may be most susceptible to AI’s spread into the economy

AI could affect work in virtually every occupational group. However, whereas research on automation’s robotics and software continues to show that less-educated, lower-wage workers may be most exposed to displacement, the present analysis suggests that better-educated, better-paid workers (along with manufacturing and production workers) will be the most affected by the new AI technologies, with some exceptions.

Our analysis shows that workers with graduate or professional degrees will be almost four times as exposed to AI as workers with just a high school degree. Holders of bachelor’s degrees will be the most exposed by education level, more than five times as exposed to AI than workers with just a high school degree.

Read more about the occupations exposed to AI on page 11 of the full report. »

Our analysis shows that AI will be a significant factor in the future work lives of relatively well-paid managers, supervisors, and analysts. Also exposed are factory workers, who are increasingly well-educated in many occupations as well as heavily involved with AI on the shop floor. AI may be much less of a factor in the work of most lower-paid service workers.

Men, prime-age workers, and white and Asian American workers may be the most affected by AI

Men, who are overrepresented in both analytic-technical and professional roles (as well as production), work in occupations with much higher AI exposure scores. Meanwhile, women’s heavy involvement in “interpersonal” education, health care support, and personal care services appears to shelter them. This both tracks with and accentuates the finding from our earlier automation analysis.

Read more about AI’s exposure levels to different demographics on page 16 of the full report. »

Bigger, higher-tech metro areas and communities heavily involved in manufacturing are likely to experience the most AI-related disruption

While AI will be employed virtually everywhere, its inroads will vary across space, determined by the local industry, education, and occupational mix. Contrary to the automation susceptibility maps, the present AI analysis reveals that smaller, more rural communities are significantly less exposed to technological disruption than larger, denser urban ones. This likely reflects the basic urban geography of the information, technology, and professional-managerial economy, with its orientation toward analytics, prediction, and strategy—all susceptible to AI. With that said, multiple metros and rural areas in the Heartland will likely contend with widespread AI given their orientation to agricultural, production, extraction, and transportation work.

Read more about which communities will be most exposed to AI on page 18 of the full report. »

In conclusion, past “automation” analyses—including our own—have likely obscured AI’s distinctive impact. Yet here too much is an open question. Most notably, this brief quantifies only the potential exposure of occupations to AI—not whether adoption has occurred or how it will affect the completion of work.

In this regard, while the present assessment predicts areas of work in which some kind of impact is expected, it doesn’t specifically predict whether AI will substitute for existing work, complement it, or create entirely new work for humans.

That means much more inquiry—qualitative and empirical—is needed to tease out AI’s special genius and coming impacts.