Abstract:

The rapid expansion of generative artificial intelligence (AI) in higher education has created new regulatory challenges worldwide since the release of ChatGPT in 2022. At the international level, responses from Anglo‑Saxon countries can be considered particularly rapid and well-coordinated. In the United States, more than 100 universities had already published guidelines on the use of AI by the summer of 2023, while in the United Kingdom the member institutions of the Russell Group formulated shared principles in the summer of 2024. In contrast, Hungarian higher education institutions reacted slowly, without unified considerations, and with varying levels of depth to the emergence of AI.

This study aims to map and comparatively analyze institutional policies governing the use of AI in Hungarian higher education. The research was conducted in autumn 2025 using a quantitative document analysis of publicly available institutional regulations. As a first step, we collected the regulatory documents available on the official websites of higher education institutions, using keyword searches when a search interface was provided, and manual review when it was not. The identified AI‑related regulatory documents were subjected to content analysis, recording the date of creation, formal characteristics (number of pages, type of document), and key thematic focus areas. The analysis of content elements was conducted through coding: categories identified during the reading of the documents were recorded in an Excel spreadsheet, followed by statistical aggregation and comparative analysis, which enabled us to reveal patterns in institutional regulatory practices.

The findings show that only 53% of higher education institutions in Hungary have adopted formal AI-related policies. However, important government regulations have contributed significantly to the steady increase in the number of regulations during the second part of the year.

The analysis of the 37 AI regulatory documents from 33 institutions reveals that these documents range from 1 to 52 pages, typically 3–7 pages, and have become increasingly complex over time. Regulating artificial intelligence in Hungarian higher education is a rapidly developing yet still emerging field, shaped by both external (governmental and quality assurance) and internal (higher‑education development centers) factors.

In line with international analyses, several key elements can be identified across institutional regulations:
i) the importance of regular updates;
ii) ethical considerations supporting academic integrity, primarily through proper source attribution;
iii) the responsibility of authors (instructors and students alike) regarding accuracy, credibility, and the avoidance of plagiarism;
iv) the expectation of protecting personal and sensitive data;
v) methodological recommendations that promote appropriate use (rather than relying on prohibition or detection); and
vi) the inclusion of application lists, usage examples, templates, and supportive training materials to facilitate practical implementation.

The analysis contributes to the harmonization and alignment of the national regulatory environment and may support the development of missing institutional AI policies in Hungary.

Keywords:

Artificial intelligence, higher education, academic integrity, regulation, AI policy.