Institutional AI policies in Ukrainian higher education: A thematic analysis and assessment using the taxonomy of institutional AI policy maturity

Type of the article: Research ArticleThe study aims to analyze institutional policies governing the use of generative artificial intelligence (GenAI) in Ukrainian universities and assess their regulatory maturity. Drawing on the authors’ Taxonomy of Institutional AI Policy Maturity (AI-PMT), which comprises twelve analytical dimensions, the study examines a sample of 23 publicly available institutional policy documents adopted between 2023 and 2025. The analysis combines qualitative and quantitative approaches. A directed content analysis was used to assign ordinal scores (0-2) across twelve dimensions, enabling the construction of a cumulative maturity index (0-24) for each institution. The results reveal an uneven distribution of regulatory development, with more elaborated provisions related to teaching and learning, and comparatively less developed components addressing research practices, data governance, and infrastructural support. To synthesize these patterns, an analytical typology of institutions was developed based on cumulative maturity scores, identifying three broad groups that differ in the degree of regulatory completeness and procedural specification. In parallel, thematic analysis of policy content identified recurring patterns, including the normalization of AI use in education, the emphasis on transparency and disclosure, the prevalence of precautionary approaches to data and confidentiality, and several contested provisions. Comparison with international policy frameworks suggests that Ukrainian universities broadly align with global normative trends in principles, but exhibit limited operationalization of governance mechanisms and research-related provisions. The findings highlight structural imbalances in institutional AI governance and underscore the need to further develop research-oriented regulation, institutional support mechanisms, and coordinated policy approaches.Acknowledgment We thank the Armed Forces of Ukraine for providing security for this work, which was made possible only thanks to the resilience and bravery of the Ukrainian Army.

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Publication Details

Journal
Knowledge and Performance Management
Published
2026-04-22
DOI
https://doi.org/10.21511/kpm.10(2).2026.01
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Institutional AI policies in Ukrainian higher education: A thematic analysis and assessment using the taxonomy of institutional AI policy maturity

Serhii Omelchuk, Yana Suchikova
Knowledge and Performance Management
Ethics and Social Impacts of AI
article

Institutional AI policies in Ukrainian higher education: A thematic analysis and assessment using the taxonomy of institutional AI policy maturity

Serhii Omelchuk, Yana Suchikova
article en

Abstract

Type of the article: Research ArticleThe study aims to analyze institutional policies governing the use of generative artificial intelligence (GenAI) in Ukrainian universities and assess their regulatory maturity. Drawing on the authors’ Taxonomy of Institutional AI Policy Maturity (AI-PMT), which comprises twelve analytical dimensions, the study examines a sample of 23 publicly available institutional policy documents adopted between 2023 and 2025. The analysis combines qualitative and quantitative approaches. A directed content analysis was used to assign ordinal scores (0-2) across twelve dimensions, enabling the construction of a cumulative maturity index (0-24) for each institution. The results reveal an uneven distribution of regulatory development, with more elaborated provisions related to teaching and learning, and comparatively less developed components addressing research practices, data governance, and infrastructural support. To synthesize these patterns, an analytical typology of institutions was developed based on cumulative maturity scores, identifying three broad groups that differ in the degree of regulatory completeness and procedural specification. In parallel, thematic analysis of policy content identified recurring patterns, including the normalization of AI use in education, the emphasis on transparency and disclosure, the prevalence of precautionary approaches to data and confidentiality, and several contested provisions. Comparison with international policy frameworks suggests that Ukrainian universities broadly align with global normative trends in principles, but exhibit limited operationalization of governance mechanisms and research-related provisions. The findings highlight structural imbalances in institutional AI governance and underscore the need to further develop research-oriented regulation, institutional support mechanisms, and coordinated policy approaches.Acknowledgment We thank the Armed Forces of Ukraine for providing security for this work, which was made possible only thanks to the resilience and bravery of the Ukrainian Army.

Knowledge and Performance ManagementVol. 10(2)
Berdyansk State Pedagogical University (UA), Kherson State University (UA)
Ministry of Education and Science of Ukraine
Openalex Percentile: Top 18%
Ethics and Social Impacts of AI
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