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Legal Regulation of Intellectual Property in the Field of Artificial Intelligence

Anzhelika Krusian1, Oleksandra Tarasenko2, Yurii Prykhodko3, Ivan Martyniuk4, Nataliia Lagovska5
1Scientific Secretary of the Institute of State and Law named after V. M. Koretsky National Academy of Sciences of Ukraine, Kyiv, Ukraine
2Department of International Law, Faculty of Political Science, Istanbul University, Istanbul, Turkey
3Department of Forensic Support and Forensic Examinations, Educational and Scientific Forensic Institute, National Academy of Internal Affairs, Kyiv, Ukraine
4Department of Intellectual Property Law and Patent Justice, National University “Odesa Law Academy”, Odesa, Ukraine
5Department of Civil Law and Procedure, Educational and Research Institute of Law, State Tax University, Irpin, Ukraine
DOI: https://doi.org/10.70517/revcc2624188
Published: 04/11/2026
: Anzhelika Krusian, Oleksandra Tarasenko, Yurii Prykhodko, Ivan Martyniuk, Nataliia Lagovska. Legal Regulation of Intellectual Property in the Field of Artificial Intelligence. Revista Cultura Científica, 2026 Issue 24. pg. 2319-2339.

Abstract

This study aimed to identify differences between contemporary approaches to protecting intellectual outputs created or used with artificial intelligence and to establish criteria connecting rights, obligations, and liability to human contributions at successive stages of the technological process. Conducted in August 2026, the study examined a purposive, non-random sample of 45 legislative, judicial, administrative, and official analytical documents from the World Intellectual Property Organization, the European Union, the United States, the United Kingdom, and Ukraine. The documentary cutoff was 27 August 2026. Documents were examined against 13 criteria encompassing input authorization, text and data mining, rights reservations, training transparency, authorship, creative control, output protection, special protection regimes, inventorship, human inventive contribution, liability, trade secrets, and remedies. European Union materials constituted 28.9% of the sample, followed by United States materials at 24.4%, United Kingdom materials at 20.0%, Ukrainian materials at 15.6%, and international institutional materials at 11.1%. The European Union instruments connect distinct mining exceptions with rights reservations and general-purpose model transparency; the United States materials emphasize fair use and case-specific analysis. United Kingdom legislation retains a computer-generated works provision, while Ukrainian legislation establishes separate protection for qualifying non-original computer-generated objects. Human contributions remain central to ordinary authorship and inventorship, although these special output regimes prevent treating that convergence as absolute. No common numerical threshold for sufficient human contribution emerged from the selected documents. The findings support a staged analysis distinguishing inputs, model operations, and outputs, with separate assessments of authorization, attribution, and responsibility. These conclusions concern the selected documentary corpus rather than an exhaustive account of every applicable rule or jurisdiction.

Keywords: generative artificial intelligence, authorship, inventorship, training data, text and data mining, intellectual property protection

Abstract

This study aimed to identify differences between contemporary approaches to protecting intellectual outputs created or used with artificial intelligence and to establish criteria connecting rights, obligations, and liability to human contributions at successive stages of the technological process. Conducted in August 2026, the study examined a purposive, non-random sample of 45 legislative, judicial, administrative, and official analytical documents from the World Intellectual Property Organization, the European Union, the United States, the United Kingdom, and Ukraine. The documentary cutoff was 27 August 2026. Documents were examined against 13 criteria encompassing input authorization, text and data mining, rights reservations, training transparency, authorship, creative control, output protection, special protection regimes, inventorship, human inventive contribution, liability, trade secrets, and remedies. European Union materials constituted 28.9% of the sample, followed by United States materials at 24.4%, United Kingdom materials at 20.0%, Ukrainian materials at 15.6%, and international institutional materials at 11.1%. The European Union instruments connect distinct mining exceptions with rights reservations and general-purpose model transparency; the United States materials emphasize fair use and case-specific analysis. United Kingdom legislation retains a computer-generated works provision, while Ukrainian legislation establishes separate protection for qualifying non-original computer-generated objects. Human contributions remain central to ordinary authorship and inventorship, although these special output regimes prevent treating that convergence as absolute. No common numerical threshold for sufficient human contribution emerged from the selected documents. The findings support a staged analysis distinguishing inputs, model operations, and outputs, with separate assessments of authorization, attribution, and responsibility. These conclusions concern the selected documentary corpus rather than an exhaustive account of every applicable rule or jurisdiction.

Keywords: generative artificial intelligence, authorship, inventorship, training data, text and data mining, intellectual property protection

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Anzhelika Krusian
Scientific Secretary of the Institute of State and Law named after V. M. Koretsky National Academy of Sciences of Ukraine, Kyiv, Ukraine
370235@ukr.net
Oleksandra Tarasenko
Department of International Law, Faculty of Political Science, Istanbul University, Istanbul, Turkey
Yurii Prykhodko
Department of Forensic Support and Forensic Examinations, Educational and Scientific Forensic Institute, National Academy of Internal Affairs, Kyiv, Ukraine
Ivan Martyniuk
Department of Intellectual Property Law and Patent Justice, National University "Odesa Law Academy", Odesa, Ukraine
Nataliia Lagovska
Department of Civil Law and Procedure, Educational and Research Institute of Law, State Tax University, Irpin, Ukraine

How to cite:

Anzhelika Krusian, Oleksandra Tarasenko, Yurii Prykhodko, Ivan Martyniuk, Nataliia Lagovska. Legal Regulation of Intellectual Property in the Field of Artificial Intelligence. Revista Cultura Científica, 2026 Issue 24. pg. 2319-2339.

Publication History

  • Received: 28/07/2026
  • Accepted: 29/10/2026
  • Published: 04/11/2026
Copyright © 2026, Anzhelika Krusian, Oleksandra Tarasenko, Yurii Prykhodko, Ivan Martyniuk, Nataliia Lagovska. Published by Revista Cultura Científica. This article is published as open access under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (http://creativecommons.org/licenses/by/4.0/).

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