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Home > Releases > Real-Time Population Survey: Generative Artificial Intelligence Adoption Tracker > Generative Artificial Intelligence, Work Hours Assisted: Utilities

Generative Artificial Intelligence, Work Hours Assisted: Utilities (RPSGENAIWORKHOURSASSI286Z)

Observations

Q2 2026: 3.14124
Updated: Aug 4, 2026 11:08 AM CDT
Q2 2026:  3.14124  
Q1 2026:  3.70141  
Q4 2025:  1.87519  
Q3 2025:  7.14713  
Q2 2025:  1.75336  

Units:

Percent,
Not Seasonally Adjusted

Frequency:

Quarterly

Fullscreen

Notes

Title Release Dates
Generative Artificial Intelligence, Work Hours Assisted: Utilities 2026-06-18 2026-06-18
 
Source    
Bick, Alexander 2026-06-18 2026-06-18
Blandin, Adam 2026-06-18 2026-06-18
Deming, David 2026-06-18 2026-06-18
 
Release    
Real-Time Population Survey: Generative Artificial Intelligence Adoption Tracker 2026-06-18 2026-06-18
 
Units    
Percent 2026-06-18 2026-06-18
 
Frequency    
Quarterly 2026-06-18 2026-06-18
 
Seasonal Adjustment    
Not Seasonally Adjusted 2026-06-18 2026-06-18
 
Notes    
This series reports the share of total work hours assisted by generative artificial intelligence among employed adults aged 18-64 in Utilities. Employed respondents who used generative artificial intelligence for their job last week report on how many workdays they used it (one, more than one, or every workday) and how much time they spent actively using it on those days (less than 15 minutes, 15 minutes to 1 hour, 1 to 4 hours, or more than 4 hours per day). Because both responses are bracketed, they imply a lower and an upper bound on assisted hours when combined with information on days worked and actual hours worked last week; this series reports the midpoint of the two bounds. Assisted hours are zero by construction for non-users. Data comes from the Real-Time Population Survey (RPS), a nationally representative online labor market survey of working-age adults aged 18-64 in the United States. When using this work, please cite: The Rapid Adoption of Generative AI, A. Bick, A. Blandin, and D. Deming, Management Science (2026) (https://pubsonline.informs.org/doi/10.1287/mnsc.2025.02523). See https://www.genaiadoptiontracker.com/ for more information.

2026-06-18 2026-06-18

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Bick, Alexander Blandin, Adam Deming, David 18 to 64 Years Survey Artificial Intelligence Working-Age Utilities Academic Data Hours Percent Employment Industry Quarterly Copyrighted: Citation Required Not Seasonally Adjusted