How does generative AI affect intellectual property rights and intangible assets?
Short Answer
Generative AI creates complex IP questions around ownership of AI-generated outputs, copyright eligibility, and whether AI-created content qualifies as a recognisable intangible asset under current accounting standards.
Full Explanation
Generative AI introduces novel challenges for intellectual property rights and intangible asset recognition. On the ownership front, most jurisdictions currently require human authorship for copyright protection — meaning purely AI-generated content may not be copyrightable, which undermines the control criterion for intangible asset recognition under IAS 38. However, AI-assisted content where humans provide substantial creative direction may qualify. For businesses, the implications are significant: if AI-generated marketing materials, product designs, or code cannot be protected by IP rights, their value as intangible assets is diminished. Companies should document the human creative contribution to AI-assisted outputs to strengthen IP claims. On the input side, training generative AI models on copyrighted material creates infringement risk — ongoing litigation (e.g., NYT v. OpenAI) may reshape what training data can legally be used, potentially reducing the value of existing training datasets. For valuation purposes, generative AI assets require careful assessment of: legal protectability of outputs, licensing terms of foundation models used, data provenance and potential infringement liability, and the competitive moat (given that similar capabilities may be broadly available). The legal landscape is evolving rapidly, making regular reassessment essential.
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Further Reading
AI and Competitive Moats: Valuing Proprietary AI Systems
Not all AI creates competitive advantage. This article examines the four types of AI moats — data, model, integration, and network — and provides a valuation framework for assessing the defensibility and durability of proprietary AI systems.
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