Can artificial intelligence systems be valued as intangible assets?
Short Answer
Yes. AI systems — including trained models, proprietary algorithms, and curated datasets — can be recognised and valued as intangible assets under both IFRS and US GAAP when they meet the standard recognition criteria.
Full Explanation
AI systems qualify as intangible assets when they meet the fundamental criteria: identifiability (the system can be separately identified, licensed, or sold), control (the entity controls access to the future economic benefits), and future economic benefits (the system generates or enhances revenue, reduces costs, or provides competitive advantage).
Under IAS 38, internally developed AI systems can be capitalised once they pass the development phase criteria: technical feasibility is demonstrated, there is intent and ability to complete the asset, probable future economic benefits exist, adequate resources are available, and costs can be reliably measured. The research phase (exploratory data analysis, algorithm evaluation) must be expensed. The development phase (model training, testing, deployment preparation) can be capitalised.
Valuation approaches for AI systems include the Cost Approach (reproduction or replacement cost of the model, data, and training), the Income Approach (present value of incremental cash flows attributable to the AI system), and the Market Approach (comparable transactions involving AI assets, though comparables are scarce). In M&A transactions under IFRS 3, acquirers must separately identify and value AI assets as part of purchase price allocation. Under US GAAP, AI built for internal use follows the internal-use software rules in ASC 350-40, which ASU 2025-06 (issued September 2025) updates from 2028; it is not AI-specific guidance.
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