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Entertainment·The Trace·Automated dual reading·Published 2026-07-20

ownership and royalty allocation for AI-generated music under intellectual property law

Source article: MANAGEMENT OF AI-GENERATED MUSIC INTELLECTUAL PROPERTY

The recent dramatic improvement of artificial intelligence (AI) in creative fields has transformed the production of music, raising complicated issues of intellectual property (IP) rights. In this paper, the author discusses the legal and ethical issues surrounding the management of AI-generated music in the current legal context. It starts by describing the concept of AI-generated music and the technology of deep-learning and neural network that makes this kind of autonomous composition possible. An analysis of…

TRV-2026-0416Peer-reviewedPermanent record — cite & verify
Trace impact reading

Contested: both sides are scored from claims and sources, not community votes.

P 66The P score combines the specificity and measured human impact of the grounded problem claim with the strength of this Trace’s cited sources.G 64The G score combines the specificity and measured human impact of the grounded gain claim with the strength of this Trace’s cited sources.
MANAGEMENT OF AI-GENERATED MUSIC INTELLECTUAL PROPERTY

"Mixing Desk" by curtis.kennington is licensed under CC BY 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by/2.0/.

The quick read

A December 2025 peer-reviewed paper in ShodhKosh examines management of AI-generated music intellectual property. It describes autonomous composition via deep-learning and neural networks, analyzes how human and AI creativity differ on intent and originality, and finds existing copyright regimes ineffective at assigning ownership and authorship to non-human creators.

The issue matters because AI has transformed music production and forces decisions about who, if anyone, owns AI outputs and how royalties should be split. The paper points to ongoing court interpretations, licensing experiments, and policy work at WIPO, EU, and U.S. agencies, but notes uncertainty remains over a balanced global framework that protects both innovation and creators' economic rights.

Main points
  • Paper defines AI-generated music as enabled by deep-learning and neural network autonomous composition.
  • Analysis finds core IP criteria of creativity, intent, and originality differ between human and AI publications.
  • Examines whether rights should belong to developer, user, or remain unprotected under current doctrine.
  • Reviews court interpretations of AI authorship across jurisdictions and cites major legal cases as practical examples.
  • Assesses policy responses from WIPO, EU, and U.S. agencies and argues for balanced global adaptation.
Gain

Proposed licensing and shared-rights frameworks for AI-generated music could equitably allocate royalties between developers and users.

Problem

Current copyright regimes are ineffective at assigning ownership and authorship for music autonomously composed by non-human AI creators.

The rundown

The paper traces how deep-learning and neural networks enable autonomous composition and contrasts human versus AI notions of creativity, intent, and originality. It critiques existing copyright regimes as ineffective for non-human creators and asks whether rights should vest in the developer, the user, or be left unprotected.

It surveys legal precedents on AI authorship across jurisdictions, discusses licensing and shared-rights ownership models, and reviews reactions from WIPO, EU, and U.S. agencies. Major legal cases are used to illustrate dispute resolution trends and the push for structures that equitably allocate royalties while preserving artistic integrity and economic justice.

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