{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T12:47:34Z","timestamp":1792673254278,"version":"4.5.0"},"reference-count":0,"publisher":"E-palli","issue":"2","license":[{"start":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T00:00:00Z","timestamp":1792627200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Am. J. Soc. L."],"abstract":"<jats:p>This paper develops a risk-based intellectual property (IP) governance framework for generative artificial intelligence (GenAI) through doctrinal, comparative, and normative analysis of the European Union (EU), the United Kingdom (UK), and the United States (US). It covers copyright and related IP challenges in data acquisition, model training, output creation, and commercial deployment, as well as the distribution of control, transparency, attribution, and liability in each jurisdiction. The analysis reveals that the EU has several text-and-data-mining exceptions and copyright-policy and training-content-summary obligations for general-purpose AI providers, while the UK has a very limited non-commercial research exception and a unique statutory exception for computer-generated works, and the US is driven primarily by the human-authorship doctrine and fact-specific fair-use analysis. While these strategies offer valuable protections, none alone establish a comprehensive system of organisational control. The study thus suggests an auditing framework linked to the legal basis, data provenance, licenses, human contribution to creativity, output testing, documentation, accountability and escalation, and periodic reassessment, according to the proportionate degree of risk. Rather than harmonizing the three legal systems, the framework sets out a common organizational process for identifying and managing differences in the three legal systems to safeguard the rights holders and to allow for responsible innovation.<\/jats:p>","DOI":"10.54536\/ajsl.v5i2.8527","type":"journal-article","created":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T12:16:30Z","timestamp":1792671390000},"page":"55-66","source":"Crossref","is-referenced-by-count":0,"title":["Developing a Risk-Based Intellectual Property Governance Framework for Generative Artificial Intelligence: A Comparative Analysis of the Eu Ai Act, Uk, and Us\u00a0Legal Systems"],"prefix":"10.54536","volume":"5","author":[{"given":"Srija","family":"Yerram","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"32981","published-online":{"date-parts":[[2026,10,22]]},"container-title":["American Journal of Society and Law"],"original-title":[],"link":[{"URL":"https:\/\/journals.e-palli.com\/home\/index.php\/ajsl\/article\/download\/8527\/4309","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.e-palli.com\/home\/index.php\/ajsl\/article\/download\/8527\/4309","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T12:16:32Z","timestamp":1792671392000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.e-palli.com\/home\/index.php\/ajsl\/article\/view\/8527"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,22]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,12,31]]}},"URL":"https:\/\/doi.org\/10.54536\/ajsl.v5i2.8527","relation":{},"ISSN":["2835-3277"],"issn-type":[{"value":"2835-3277","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,22]]}}}