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When Music is Made by AI: Effects on Preferences and Willingness to Pay

Author

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  • Jana Friedrichsen
  • Julia Schwarz
  • Michel Clement

Abstract

Artificial intelligence (AI) is rapidly reshaping society, including the music industry. Recent advancements in generative AI enable users to create music from text-based prompts, raising questions about public perception and valuation of AI-generated music. We conducted three studies with German-speaking participants (Study 1: N=2000, Study 2: N=425; Study 3: N=1248) to explore awareness, enjoyment, and willingness to pay for AI music. After finding no clear rejection of AI composed music in Study 1, Study 2 varied whether listeners knew the music was AI-generated. Study 3 involved regular listeners of pop and electronic dance music, manipulating song origin (human vs. AI) and disclosure. Results show that listeners generally could not distinguish between AI and human-made songs. When unaware, participants slightly preferred AI music and valued it equally. However, disclosing that AI had been used to create compositions reduced appreciation and willingness to pay. We explore how reactions differ by genre and individual attitudes toward AI and discuss implications for the music industry and for regulatory initiatives.

Suggested Citation

  • Jana Friedrichsen & Julia Schwarz & Michel Clement, 2026. "When Music is Made by AI: Effects on Preferences and Willingness to Pay," CESifo Working Paper Series 12405, CESifo.
  • Handle: RePEc:ces:ceswps:_12405
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    1. Muhammad Umair Shah & Umair Rehman & Bidhan Parmar & Inara Ismail, 2024. "Effects of Moral Violation on Algorithmic Transparency: An Empirical Investigation," Journal of Business Ethics, Springer, vol. 193(1), pages 19-34, August.
    2. Frederik Juul Jensen, 2024. "Rethinking royalties: alternative payment systems on music streaming platforms," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 48(3), pages 439-462, September.
    3. Regner, Tobias & Barria, Javier A., 2009. "Do consumers pay voluntarily? The case of online music," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 395-406, August.
    4. David A. Spencer, 2023. "Automation and Well-Being: Bridging the Gap between Economics and Business Ethics," Journal of Business Ethics, Springer, vol. 187(2), pages 271-281, October.
    5. Dufwenberg, Martin & Kirchsteiger, Georg, 2004. "A theory of sequential reciprocity," Games and Economic Behavior, Elsevier, vol. 47(2), pages 268-298, May.
    6. Tubadji, Annie & Huang, Haoran & Webber, Don J, 2021. "Cultural proximity bias in AI-acceptability: The importance of being human," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    7. Santiago Mejia, 2023. "The Normative and Cultural Dimension of Work: Technological Unemployment as a Cultural Threat to a Meaningful Life," Journal of Business Ethics, Springer, vol. 185(4), pages 847-864, July.
    8. Frederik Juul Jensen, 2024. "Rethinking royalties: alternative payment systems on music streaming platforms," Post-Print hal-04885870, HAL.
    9. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    10. Carlo Ludovico Cordasco & Carissa Véliz, 2025. "Self-Esteem and Technological Unemployment: Should We Halt AI to Protect Meaningful Work?," Journal of Business Ethics, Springer, vol. 202(1), pages 21-33, November.
    11. Max J. Pachali & Hannes Datta, 2025. "What Drives Demand for Playlists on Spotify?," Marketing Science, INFORMS, vol. 44(1), pages 54-64, January.
    12. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    13. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    14. Abel, Martin & Johnson, Reed, 2025. "AI Bias for Creative Writing: Subjective Assessment Versus Willingness to Pay," IZA Discussion Papers 17646, IZA Network @ LISER.
    15. Janek Meyn & Michael Kandziora & Sönke Albers & Michel Clement, 2023. "Consequences of platforms' remuneration models for digital content: initial evidence and a research agenda for streaming services," Journal of the Academy of Marketing Science, Springer, vol. 51(1), pages 114-131, January.
    16. Sarah Bankins & Paul Formosa, 2023. "The Ethical Implications of Artificial Intelligence (AI) For Meaningful Work," Journal of Business Ethics, Springer, vol. 185(4), pages 725-740, July.
    17. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
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    Cited by:

    1. Bernd Irlenbusch, 2026. "Human Trust in AI: Evidence from Experimental Economics," ECONtribute Discussion Papers Series 417, University of Bonn and University of Cologne, Germany.

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    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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