As companies expand their investment in artificial intelligence, intangible assets are drawing growing attention as a source of corporate value. In the past, tangible assets such as factories and equipment were at the core of corporate competitiveness. In the AI era, what matters is how to identify and manage the corporate value created outside the financial statements.
According to the World Intellectual Property Organization (WIPO), intangible asset investment across 29 major countries surpassed $10 trillion in 2025 and has grown 3.6 times faster than tangible asset investment since 2008. Most of that value, however, does not appear on the books. Brand Finance estimated the intangible asset value of listed companies worldwide at $97.6 trillion last year and found that 83% of it is not reflected in financial statements.
Generative AI is accelerating this shift. Companies are giving AI tools to their employees, attaching chatbots to customer service and automating contract reviews and data analysis. In the process, knowledge about which materials to trust, which risks to check and when expert judgment is required becomes an asset. Refined data, algorithms, prompts and rule sets, along with experts' criteria for judgment and customer feedback, can all become new intangible assets.
The question is who holds ownership of these intangible assets and the value they carry. Multiple parties take part in building AI assets, including foundation model providers, system integrators, and a company's own employees and customers. Depending on who owns the datasets and business logic created along the way, and on whether the company can continue to use them after a contract ends, AI investment may remain a corporate asset or amount to nothing more than a service fee.
For multinational companies in particular, deciding which country or entity should be credited with the value and profits generated by AI is complex. A Korean head office may have designed an AI platform while an overseas subsidiary supplied local data and market knowledge, or an overseas development center may have implemented the technology while the head office handled the core business logic and risk controls.
This leads to transfer pricing questions about how to allocate platform usage fees, compensation for data provision, joint development costs and returns on intangible assets between the head office and overseas subsidiaries. The transfer pricing principles of the Organisation for Economic Co-operation and Development (OECD) also maintain that compensation between related parties should align with actual economic activity and value creation rather than with the title of a contract.
The results of AI investment are therefore difficult to assess based on adoption costs or operational efficiency alone. Companies must also examine whether the data and business knowledge accumulated inside the organization remain assets that can be used on a continuing basis, and whether the value and profits flow to the parties that actually contributed.