What question did this study set out to answer?

The aim is to characterize generative AI application usage among US youth, including adoption rates and time spent on apps.

February 5, 2026Open Access

Generative Artificial Intelligence Applications Use Among US Youth

AMAnne J. MaheuxUniversity of North Carolina at Chapel Hill SASamir AkreUniversity of California, Los Angeles DBDebra BoeldtAssociation pour l'Utilisation du Rein Artificiel

Key Points

The aim is to characterize generative AI application usage among US youth, including adoption rates and time spent on apps.
Cross-sectional study design
Participants aged 4 to 17 years from families using the Aura app
Data collected through passive sensing methods
Digital behavior analyzed between September 2024 and April 2025
31.9% of participants accessed generative AI apps
Usage was highest among teens aged 13 to 17 years, with as high as 50.4%
Usage after school was more common than at night or during school hours
Mean daily time spent on GenAI was 2.37 minutes, but some used it for over 40 minutes daily

Abstract

Importance As generative artificial intelligence (GenAI) tools become increasingly integrated into the daily lives of youth, it is critical to study their usage patterns and potential implications for mental health. While there is evidence of a rapid pace of adoption among adults, rates of GenAI use among youth remains largely undocumented. Objective To characterize GenAI application (app) usage among US youth, including adoption rates and time spent. Design, Setting, and Participants This cross-sectional study documented digital behavior of US youth extracted from a parental monitoring app. Participants were ages 4 to 17 years and were in families using a commercially available Aura app in the US. No identifying information was collected about the child except year of birth. Data were collected using passive sensing methods from naturalistic smart device use between September 2024 and April 2025. Data were analyzed in May and June 2025. Main Outcome and Measures Adoption rates (ie, number of youth ever accessing GenAI apps on their device) and time spent using GenAI (ie, average minutes accessing GenAI apps), measured by age and time period. Results In a cohort of 6488 participants, nearly 2072 youths (31.9%) used GenAI apps on their device. GenAI use was highest among teens (age 13 to 14 years, 899 of 2139 42.0%; age 15 to 17 years, 628 of 1246 50.4%), although adoption among preteens (age 10 to 12 years, 484 of 2366 20.5%) and school-aged children (age 8 to 9 years, 49 of 522 9.4%) was not trivial. GenAI usage was higher after school than at nighttime or during school. Overall, users spent a mean (SD) 2.37 (10.55) and a median (IQR) 0.18 (0.04-0.84) minutes a day using GenAI, yet large variances and skewed distributions suggest that a small subset of youth use GenAI extensively, with the heaviest users accessing GenAI for over 40 minutes a day. Conclusions and Relevance In this cross-sectional study, Gen AI app use varied widely among participants, with up to half of adolescents having some use and a small subset engaging in heavy use. Future research must address individual differences in GenAI use to determine impacts on development.

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