<p>When Copyright Becomes Credit Risk: Artificial Intelligence and Intangible Asset Financing</p>

Discussions on the impact of artificial intelligence on copyright law have largely focused on infringement, fair use, authorship and the permissibility of training models on protected works. These debates often unfold at the level of doctrine or ex post liability. However, the rapid growth of intangible asset financing requires a shift in perspective. As intellectual property is increasingly used as collateral and securitized in financial transactions, copyright uncertainty assumes new commercial significance at the pre-transaction stage. What has received far less attention is how copyright uncertainty, particularly in AI-mediated assets, filters into pre-transaction due diligence. This uncertainty gets commercially sensitive, especially where intellectual property is relied upon as collateral or is the subject of securitization. In such context, copyright infringement is not merely a legal concern, it becomes a determinant of valuation, bankability, and credit risk. As AI systems increasingly rely on data-intensive architectures, copyright questions are migrating from the margins of enforcement into the core of transactional risk assessment. Historically, copyright law occupied a relatively modest place in transactional due diligence when compared to patents or registered rights. While ownership and chain of title have always mattered, infringement risk was often treated as contingent, arising from specific uses rather than from the existence of the asset itself. A software programme for instance cannot be a topic of copyright infringement for existing, unless it has been used in a way not authorized. In most cases, copyright risk could be managed operationally, usually through licensing, takedown procedures or adjustments to modes of exploitation. As a result, copyright rarely threatened the fundamental financeability of an asset. However, the operation of AI destabilizes this assumption. The infringement question may arise now from the model's formation rather than its deployment. This is to say that infringement risk becomes inherent in the model's formation, making it difficult to predict or control when protected expression may be reproduced, thereby placing copyrighted works at risk of unauthorized use. Where an AI-system is trained without authorization and its generated outputs serve as functional substitutes in the consumption market, they introduce uncertainty into the original asset's future revenue stream. The question now is whether the original asset's economic value can still be said to subsist. Can the streaming revenue remain substantial enough to stand as collateral for financial arrangement? This paper demonstrates how copyright infringement by artificial intelligence reduces the economic reliability of intellectual property for purposes of collateralization, securitization, and sale-and-lease-back structures. Likewise, it clarifies what differences obtain between AI-driven companies and right holders, and what financial implication the infringement has on both of them. Furthermore, the paper demonstrates how the IP-backed financial structures work with copyright. Finally, it looks into the effects of the infringement on copyright and what pre-transaction due diligence will be like for investors and financiers.