VALUATION OF INTANGIBLE ASSETS IN THE DIGITAL ECONOMY

Abstract

In the digital economy, intangible assets such as proprietary data, network effects, and tokenized intellectual property (IP) often constitute over 80% of a firm’s market value. However, traditional accounting standards (IFRS/US GAAP) frequently fail to capture these “hidden” values. This study analyzes the shift from cost-based to fair-value-based valuation methods. The results indicate that integrating AI-driven predictive analytics and real-time market data provides a more accurate representation of digital asset value than historical cost models.