AI Solutions Poised to Drive Advancement in Real-World Asset Tokenization
The crypto industry is looking to capitalize on the tokenization of real-world assets (RWAs) as the next major use case for blockchain technology. According to a report released by investment bank Citi in March 2023, the market for RWAs is projected to reach $4 trillion to $5 trillion by 2030. While the potential for tokenization is transformative, mass adoption has yet to be achieved. However, industry experts believe that artificial intelligence (AI) solutions could play a crucial role in advancing the use cases for tokenized RWAs.
Tokenized RWAs differ from previous security token offerings (STOs) that were largely unregulated. Dave Hendricks, CEO and Co-founder of Vertalo, a digital transfer agent and enterprise software platform, explains that tokenized RWAs now have a degree of tangibility. Assets like art, diamonds, and real estate can now be fractionalized through tokenization, allowing investors to own a percentage of the asset and receive income from its use or lease.
Tokenized RWAs offer several benefits, including increased tradability and transparency, as well as improved mid/back-office applications within traditional asset management functions. Large financial institutions, such as BlackRock and Mastercard, have already shown interest in improving their asset management functions using distributed ledger technology and tokenized asset settlement.
AI can further enhance the use cases for tokenized RWAs. For example, AI can enable asset value prediction, helping venture capitalists predict the future values of their assets and RWAs. This can lead to better valuations of RWA tokens. AI can also be used to streamline pricing determinations for tokenized RWAs, especially for assets with limited pricing information. Additionally, AI can automate RWA workflow analysis, improving the reliability of smart contracts and detecting potential bugs and compliance issues.
However, challenges remain for the adoption of tokenized RWAs and AI. Limited data access can hamper the usability of AI applications, and the lack of Know Your Customer (KYC) procedures in decentralized exchanges may impact customer risk assessments. Regulatory issues and asset verification also pose challenges for tokenized RWAs. Tokenizing an asset may subject it to strict regulatory scrutiny, and verifying the authenticity of the assets underlying RWA tokens can be problematic.
Despite these challenges, tokenized RWAs have the potential to revolutionize the financial industry. By carefully structuring tokenized RWAs and leveraging AI solutions, the industry can overcome obstacles and unlock the full potential of this innovative technology.
