AI and blockchain are two major technologies accelerating their collision and integration. One is known for decentralization, transparency, and immutability, while the other excels in data analysis, pattern recognition, and intelligent decision-making. Although they seem different, they can actually complement each other—blockchain needs stronger risk control capabilities, and AI lacks trustworthy data sources; together, they form a perfect match.

Market data is quite interesting. In 2024, this market is valued at $570 million, growing to $700 million by 2025, and expected to reach $1.88 billion by 2029. Looking from another perspective, the compound annual growth rate exceeds 23%, indicating that this track is really gaining momentum.

Let's start with the most direct application—fighting fraud. Blockchain processes massive amounts of transactions daily, but problems are obvious: money laundering, identity theft, suspicious transfers—these happen every day. How does AI solve this? By analyzing transaction behavior through machine learning algorithms, it can flag anomalies as soon as they occur.

Elliptic, MIT, and IBM have launched a collaborative project, training models on over 200 million encrypted transactions, resulting in a significant improvement in anomaly detection accuracy. Even more impressive, IBM’s blockchain research team reported that their AI-driven anomaly detection system, during pilot tests, directly reduced settlement fraud by over 80%. This number sounds a bit exaggerated, but from the perspective of the stability of distributed financial networks, it indeed solves a major problem.

In DeFi, the value of AI becomes even more apparent. Intelligent systems can detect potential money laundering activities, internal trading patterns, and then flag suspicious operations in real-time. Risks are identified before they escalate. This is of great significance for the healthy operation of the entire ecosystem.