Starting at the end of 2023, artificial intelligence (AI) and real world assets (RWA) have become the key narratives driving the next bull market in the crypto space. RWA is a category of blockchain-based crypto tokens that represent tangible or intangible assets such as bonds, real estate, and commodities. RWA enables these assets to be traded through decentralized finance (DeFi), thereby increasing the availability of these usually inaccessible financial instruments and opening up new application prospects. It is currently estimated that by 2030, the market size of RWA and AI will reach US$4 trillion to US$5 trillion and US$738.8 billion, respectively.
This article will focus on the synergy between these two emerging fields and analyze how they can cooperate with each other and reshape the future.
AI’s Path to RWA
First, AI models, especially advanced models like GPT-4, represent the highest level of innovation in natural language processing and machine learning. Their development requires significant investments in cutting-edge algorithms, large-scale datasets, and vast computing resources. When these models are fine-tuned for specific industry applications, their value increases significantly. In addition, the large amount of data used to train these models is not only a treasure trove of information, but also a highly valuable asset in itself. In addition, AI technology and its underlying intellectual property, including patents and copyrights, provide unique profit opportunities for their creators or owners. Therefore, AI models, training data, and the intellectual property that protects them can be considered high-end RWA.
AI’s Path to RWA
The power of AI is reshaping all industries, and it is a crucial tool for the formation of RWA, which is reflected in the following aspects:
Enhanced security: The role of AI in cybersecurity cannot be overstated. In particular, AI systems can continuously monitor and analyze transaction data, identifying signs of unusual activity that could indicate a security threat. These systems are able to detect patterns and anomalies that humans might miss, such as subtle signs of fraudulent transactions or early signs of a cyberattack. Once a potential threat is identified, AI can take immediate action to neutralize it, such as blocking suspicious transactions or isolating affected systems to prevent further damage. This proactive security approach helps maintain the integrity and trustworthiness of RWA services.
Enhanced user privacy: Privacy issues are a primary concern for RWA transactions. AI improves privacy by using more sophisticated encryption techniques that are more difficult for unauthorized parties to crack. In addition, AI can use methods such as biometric verification (facial recognition, fingerprint) to manage and verify user identities with greater accuracy and less interference, adding an additional layer of security. With the support of AI, user data can be kept confidential and secure, greatly reducing the risk of data breaches and identity theft.
Assisted decision making and market prediction: Financial markets, including the RWA trading platform, are known for their volatility and complexity. AI excels at analyzing large amounts of market data, including past trading volumes, price movements, and economic indicators, to identify trends and patterns in future market behavior. This analysis can be extended to global events, social media sentiment, and other external factors that affect the market. With these insights, AI is able to provide traders and investors with information on market trends, with the ability to identify favorable trading opportunities or warn of potential downside risks. This ability is invaluable for trading decisions, maximizing investment returns and minimizing risks.
In summary, by leveraging the diverse capabilities of AI, the security, privacy, and operational efficiency of real-world asset services can be greatly improved. This not only helps service providers reduce risks and improve customer satisfaction, but also enhances user experience by providing a safer, more reliable, and more efficient trading and investment platform.
As AI technology advances, its role in RWA services is expected to become more important, driving innovation and creating new opportunities in the crypto space and beyond. However, this integration also faces challenges. The opacity of AI algorithms and the potential systemic risks posed by their vulnerabilities require the development of trustworthy and transparent AI solutions. In other words, this will make decentralized AI an important trend in the future, including the complete AI deployment cycle including data collection, preprocessing, and model training.
Author: Dr. Chong Li, Founder of OORT and Professor of Columbia University
Originally published in Forbes:
