This article addresses three critical policy questions that will determine the impact of generative AI on the knowledge economy and the creative sector. The first concerns how we think about the training of such models — in particular, whether the creators or owners of the data that are “scraped” (lawfully or unlawfully, with or without permission) should be compensated for that use. The second question revolves around the ownership of the output generated by AI, which is continually improving in quality and scale. These questions are inherently linked to the realm of intellectual property, a legal framework designed to incentivize and reward human creativity and innovation. For instance, the United Kingdom has historically maintained a distinct category with limited rights for new “computer-generated” works, while Singapore recently introduced an exemption allowing for computational data analysis of existing works. The third section of this article explores the broader implications of these policy choices, weighing the advantages of reducing the cost of content creation and the value of expertise against the potential risks to various careers and sectors of the economy, which may be rendered unsustainable. Some lessons might be found in the music industry, which also went through a period of unrestrained piracy in the early digital era, epitomized by the rise and fall of the file-sharing service Napster. Similar litigation and legislation may help navigate the present uncertainty, along with an emerging market for “legitimate” models that respect the copyright of humans and are clear about the provenance of their own creations.