Abstract

Generative artificial intelligence systems (generative AI systems) and within that, large language models (LLMs), have become particularly valuable in recent years. Their impact is growing, and they are undergoing significant development, which is also having a major impact on the legal profession and legal education.

In this presentation, I will present the aims, attitudes, and habits of law students in relation to the use of generative AI systems, based on the results of quantitative empirical research. The first survey was conducted in 2025 with the participation of 187 law students at the Faculty of Law and Political Sciences of the University of Szeged, Hungary. Given the extremely rapid spread and development of the technology, the survey will be conducted again in the spring of 2026. This presentation outlines the main survey findings. The research focused particularly on gender-based comparisons of responses. A significant difference exists between the responses of female and male law students regarding how willing they are (or would be) to use generative AI systems in their legal work, with female law students being less willing. Furthermore, there is a significant difference between female and male law students in terms of their assessment of technological knowledge, acquisition and their approach to this technology.

According to the results’ of 2025, 81% of the students had used generative AI systems mainly for learning, text generation, and entertainment. 35% of the users have been using a generative AI system for 1-2 years, 23% of them have been using it for at least two years, 42% of them who have used a generative AI system, have been using it for less than 1 year. Regarding magnitude of the reluctance to use generative AI systems, a significant difference can be established with respect to different purposes of use, for example, 39.46% of the respondents show no reluctance whatsoever toward using them for general, everyday topics, whereas in the case of professional (legal) use, this proportion is 11.89%.

Insights into students’ aims, attitudes, and habits are crucial for enhancing AI literacy in both the present and the near future.