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Digital Rights Management and AI Licensing in the Creative Industries: Mapping the Emerging Digital Licensing Ecosystem
Abstract
Generative AI is shifting digital rights management from access control to managing an ongoing rights relationship across training, inference, and output. Addressing linked challenges in provenance, identification, attribution, licensing, remuneration, and enforcement, this working paper maps organizations and institutions across music, news, and audiovisual media. Structured across seven technological domains and ecosystem frameworks, the paper highlights a central "integration gap": specialist tools exist for distinct stages, but no universal workflow connects provenance to creator payment. The study provides an orientation framework to move from a fragmented ecosystem towards an integrated, scalable digital licensing ecosystem.
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Metadata
- Authors
- Wellen, N., Hannemann, J.-G. A., & Tietze, F.
- Venue
- Apollo - University of Cambridge Repository
- Publisher
- Apollo - University of Cambridge Repository
- Published
- 2026-09-09
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- CoChat. (2026). Citation check: Digital Rights Management and AI Licensing in the Creative Industries: Mapping the Emerging Digital Licensing Ecosystem. https://app.cochat.ai/papers/10.17863/cam.134189
- The paper
- Wellen, N., Hannemann, J.-G. A., & Tietze, F. (2026). Digital Rights Management and AI Licensing in the Creative Industries: Mapping the Emerging Digital Licensing Ecosystem. Apollo - University of Cambridge Repository. https://doi.org/10.17863/cam.134189
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
