Early and late adoption and appropriation of LLMs differs by gender, age, and technology education

This is the authors' abstract. We don't add key points for this paper.

Large Language Models (LLMs) have become increasingly integrated into critical activities of daily life. This raises concerns about equitable access and utilization across diverse demographics. This study investigates the adoption and usage of LLMs in two waves of a survey with a quota-based U.S. sample ( , ). The share of respondents who reported utilizing an LLM rose from 42 % in 2023 to 82 % in 2025. We found a gender gap in early LLM adoption (more male than female users) with complex interaction patterns regarding age and technology education as a mediator. Over time, the gender gap for usage disappeared, but male users were still more frequent users and rated their perceived competence as higher. Common usage scenarios show an increase in information search and editorial use as opposed to a decrease in entertainment purposes and experimental use. Adoption barriers include a lack of knowledge and need, privacy, and ethical concerns. These results underscore the importance of providing education in artificial intelligence in our technology-driven society to promote equitable access to and benefits from LLMs.