<![CDATA[The rapid proliferation of artificial intelligence (AI) technologies has created a significant gap between corporate economic reality and financial statement disclosure. While firms invest billions of dollars in AI systems, current accounting standards primarily IAS 38 (Intangible Assets) and IAS 16 (Property, Plant and Equipment) were not designed to accommodate the unique characteristics of AI assets. This paper conducts a systematic literature review of 20 peer-reviewed studies published between 2021 and 2024 to examine the challenges of recognising and measuring AI as a corporate asset. The findings identify five critical challenge domains: (1) recognition criteria ambiguity, (2) measurement model insufficiency, (3) rapid obsolescence, (4) data valuation complexity, and (5) ethical and disclosure deficiencies. We propose a five-tiered AI asset classification framework aligned with existing IFRS principles and provide guidance on recognition, measurement, and impairment testing. The study concludes that standard-setters, including the IASB, must urgently revisit intangible asset standards to reflect the economic substance of AI investments and ensure transparent, comparable financial reporting.]]>
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