Patents, Profits, and Machines: How AI Is Reshaping Innovation and Taxation
Patents, Profits, and Machines: How AI Is Reshaping Innovation and Taxation

Summary/Abstract: Patents grant inventors exclusive rights, fostering innovation while playing a crucial role in global tax strategy. Multinational corporations often exploit patent-related tax advantages by shifting intellectual property to low-tax jurisdictions, raising concerns over tax base erosion. Patent boxes, used by countries like the UK and Netherlands, offer reduced tax rates to stimulate R&D but face scrutiny from international bodies like the OECD, which promotes tighter regulations through initiatives like the BEPS Action Plan. Transfer pricing of patents remains contentious due to the difficulty of valuing intangible assets. The emergence of AI in innovation introduces further complexity as AI systems increasingly meet patent criteria, challenging current legal definitions that restrict inventorship to humans. High-profile cases like DABUS underscore the urgency of updating legal frameworks to address AI-generated inventions.Additionally, AI is transforming how patents are evaluated and enforced, enhancing efficiency while raising ethical concerns around transparency and accountability. These developments affect income attribution, valuation, and regulatory compliance.In order to address these shifts, policymakers must clarify inventorship laws, develop global standards, reform tax guidelines, ensure AI transparency, and empower regulatory agencies with AI tools. As AI reshapes innovation, the intersection of patent law and taxation must evolve to ensure fairness and effectiveness in this new landscape. Governments face significant challenges in addressing transfer pricing for AI-generated assets, particularly due to the risk of profit shifting by multinational companies to low-tax jurisdictions. To counter these issues, reforms are being proposed, including modernizing intellectual property tax rules to reflect the role of non-human creators and strengthening transparency requirements across AI-driven value chains.

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