AI Copyright Conundrum: How UK Law Struggles to Balance Creator Rights and Technological Innovation

Introduction

Intellectual property law is an incentive system– that means, the law goes beyond a mere protection of the author’s ownership of creations and encourages continued creativity and innovation. [1] However, the emergence of artificial intelligence (‘AI’), particularly generative AI systems capable of producing text, images, and music, has created a fundamental tension within this framework. The preservation of incentives for human creators conflicts with the promotion of the development and deployment of AI. This essay particularly examines the copyright challenges emerging from AI in the UK, and considers the future implications for both AI developers and original creators.

UK Copyright Law Framework

The UK Parliament’s legislature, Copyright, Designs and Patents Act 1988 (the ‘CDPA’), was the first in the world to have considered copyright in the context of AI. Section 9(3) reads, ‘in circumstances such that there is no human author of the work’, the author ‘shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken’. [2] This approach to protecting works generated by a computer has been adopted by only a small number of jurisdictions, making the UK a unique jurisdiction in this regard. Despite its foresight, the UK’s protection of computer-generated works poses several conspicuous challenges. [3] The current UK copyright law prohibits the use of copyright works for development without a license, whereas the exemption may apply for non-commercial research. [4] In the context of AI, two main issues arise– the development of AI while using copyrighted works, and the copyright of the computer- generated works themselves. These questions expose structural limitations in the existing regime, which was not designed with autonomous generative technologies in mind. [5] Similar concerns have been identified in academic literature, which argues that machine learning challenges the foundational assumptions of copyright law regarding copying and creativity. [6]

Legal Precedent and Challenges

Recent litigation further illustrates these uncertainties. Getty Images v Stability AI was one of the most anticipated cases regarding copyright infringement in the UK, [7] in which the claimant alleged that their copyrighted images were used to train the defendant’s AI model without permission.

Although aspects of the litigation have been favorable to AI developers, the case did not resolve the uncertainty regarding whether AI training constitutes infringement under UK law, partly because much of the training occurred outside the jurisdiction. This uncertainty has broader implications. AI developers may interpret the legal landscape as encouraging training activities outside the UK to minimize legal risk. [8] Such regulatory arbitrage could discourage domestic investment in AI development while simultaneously limiting remedies available to UK rights holders whose works are used abroad. More broadly, uncertainty undermines both sectors: creators face concerns about uncompensated use of their work, while developers lack clarity regarding permissible conduct. Rather than supporting innovation, ambiguity risks suppressing it.

Copyright Law Reform?

Recognizing such uncertainties, the UK government has begun considering possible solutions in response to the emergence. [9] The ongoing consultation stage has explored mechanisms, such as a copyright exemption for AI developers, or an opt-out model, whereby copyright holders would retain the ability to prevent use of their works. [10]

Survey responses suggest strong support among rights holders for mandatory licensing arrangements requiring AI developers to pay for access to copyrighted materials, while technology companies have generally favored more permissive approaches. [11] These divergent preferences highlight the central policy dilemma: the balancing between the right holders’ control of their content and ability to be remunerated for its use, and the enhancement of the development of world-leading AI models in the UK by ensuring wide and lawful access to high-quality data.

Achieving an outcome that satisfies both sectors' demands is inherently difficult. Strengthening rights holders’ control may protect creative industries but risks imposing barriers to technological innovation, while broad exceptions may accelerate AI development at the cost of undermining incentives for human creativity. The challenge for policymakers is therefore not to eliminate this tension, but to manage it through a framework that provides legal certainty, fair remuneration, and practical accessibility.

Conclusion

Legal uncertainty surrounding both AI training and AI-generated outputs risks negative consequences for creators and developers alike, potentially reducing investment in creative industries while discouraging technological innovation within the UK. Considering these challenges, the government must establish a clear and balanced legal framework that supports sustainable growth in both sectors. Human creativity and AI innovation should not be viewed as competing objectives, but as complementary forces that together drive economic and cultural progress.

References

[1] William M Landes and Richard A Posner, ‘An Economic Analysis of Copyright Law’ (1989) 18 Journal of Legal Studies 325.

[2] Copyright, Designs and Patents Act 1988, s 9(3).

[3] Toby Bond and Sarah Blair, ‘Artificial Intelligence & Copyright: Section 9(3) or Authorship without an Author?’ (2019) 14(6) Journal of Intellectual Property Law & Practice 423 <https://doi.org/10.1093/jiplp/jpz056> accessed 16 February 2026.

[4] Copyright, Designs and Patents Act 1988, ss 16–17, 29A.

[5] Andres Guadamuz, ‘A Scanner Darkly: Copyright Liability and Exceptions in Artificial Intelligence Inputs and Outputs’ (2024) 73 GRUR International 111.

[6] Daniel J Gervais, ‘The Machine as Author’ (2020) 105 Iowa Law Review 2053.

[7] [2025] EWHC 2863 (Ch)

[8] Browne Jacobson, ‘Getty Images’ Copyright Not Infringed by Stability AI Making Its Stable Diffusion Model Available to Users in the UK’ (12 November 2025) <https://www.brownejacobson.com/insights/getty-images-stability-ai-judgment-uk-copyright-law-analysis> accessed 16 February 2026.

[9] Department for Science, Innovation and Technology and Department for Culture, Media and Sport, Copyright and Artificial Intelligence (Consultation Paper, CP 1205, 2024) <https://www.gov.uk/government/consultations/copyright-and-artificial-intelligence/copyright-and-artificial-intelligence#ministerial-foreword> accessed 16 February 2026.

[10] Ibid (n 6)

[11] Department for Science, Innovation and Technology and Department for Culture, Media and Sport, Copyright and Artificial Intelligence: Statement of Progress under Section 137 Data (Use and Access) Act (Intellectual Property Office, 15 December 2025) <https://www.gov.uk/government/publications/copyright-and-artificial-intelligence-progress-report/copyright-and-artificial-intelligence-statement-of-progress-under-section-137-data-use-and-access-act> accessed 16 February 2026.

Image Credits

Steve Johnson on Unsplash <https://unsplash.com/photos/a-computer-circuit-board-with-a-brain-on-it-_0iV9LmPDn0>