Algorithmic Ownership in the Age of Generative Artificial Intelligence: Reconciling Intellectual Property Regimes with Sociotechnical Imperatives

Arjit Kandalai

doi:10.36948/ijfmr.2026.v08i02.71900

Algorithmic Ownership in the Age of Generative Artificial Intelligence: Reconciling Intellectual Property Regimes with Sociotechnical Imperatives

Author(s)	Mr. Arjit Kandalai
Country	United States
Abstract	The emergence of generative artificial intelligence systems has triggered some underlying tensions in the traditional intellectual property systems. The article contributes to a systematic study of the way the tripartite architecture of modern AI systems underlying code, trained models, and training data are facilitated or not in trade secret doctrine, copyright law, and patent regimes. Based on the comparative legal analysis of the European Union and the United States jurisdictions, with the support of the empirical evidence of the cross-sectoral data-sharing practices, this inquiry indicates that there are significant gaps in the doctrines that need to be addressed both in scholarship and legislation. The discussion shows that trade secret protection, even though it maintains competitive advantages, also hinders the need to promote transparency and fair value distribution processes required to ensure responsible AI governance. The copyright laws do not manage to deal with the magnitude of training data consumption, and the authorship disputes over machine-generated products. The patent doctrine, which is based on human inventorship, faces inadmissible contradictions in case artificial systems play a significant role in the innovative process. In this article, the hybrid architecture of governance is suggested, which comprises a combination of balanced intellectual property protection with open science and collective data stewardship models. Some of the specific proposals include standardized data-sharing contractual models, obligatory AI contribution disclosure in patent applications, revamped text-and-data mining exemptions, sui generis protection of AI-generated works, and institutional structures of democratic data regulation. These reforms are proposed to support incentives of innovation with promoting transparency, accountability, and the fair allocation of artificial intelligence-derived benefits in society.
Keywords	Artificial intelligence; Intellectual property; Algorithmic governance; Data commons; Trade secrets; Copyright; Patent law; Open science; Generative AI; Digital ownership
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-26
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.71900

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Algorithmic Ownership in the Age of Generative Artificial Intelligence: Reconciling Intellectual Property Regimes with Sociotechnical Imperatives

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