AI & DeFi: The Next Financial Evolution in Crypto Investing

Exploring the Future of DeFi with AI-Driven Innovations

Artificial intelligence was first conceptualized back in the 1950s, and it has taken almost 70 years for the technology to become accessible to anyone but a few scientists and rich organizations. 

But now that has happened, the use of AI is being implemented far and wide. In decentralized finance, it has progressed beyond a buzzword to become a vital tool that can ensure a superior user experience and better outcomes for every user. But the integration of AI and DeFi has only just begun, and in the next few years, it’s going to transform every single aspect of this fast-growing industry.  

Rapid growth on the horizon 

The use of AI in financial technology has exploded, and the market for these tools is set to grow to $39.1 billion by 2032, up from just $9.6 billion in 2022, according to a report by Market Research Future. These numbers suggest that AI has already moved on from the experimental stage and is fast becoming an essential element of fintech, and research from McKinsey supports this idea, noting that two-thirds of organizations globally had already embraced the technology in a business capacity in 2024. 

Moreover, the rise of DeFi itself is likely to be even more remarkable, with Mordor Intelligence forecasting it to grow to more than $87 billion by the end of 2030. 

With regard to AI’s adoption in DeFi, we’re only just beginning to see the first use cases arising from the intersection of these two technologies. Most DeFi projects have only just begun exploring AI applications, using it to help optimize liquidity, improve efficiency and risk management, and in predictive analytics. They’re promising ideas, but AI’s potential in DeFi stretches well beyond those implementations. 

How is AI being used in DeFi today?

DeFi protocols are putting AI to use in several different ways. Aave, one of the most prominent decentralized lending protocols, uses AI-powered algorithms to dynamically adapt its interest rates based on real-time market conditions. Its system is designed to ensure both borrowers and lenders benefit from competitive rates, so both parties are incentivized to continue using the protocol. In future, Aave hopes to introduce AI-powered credit systems that will work by analyzing user’s transaction histories to try and establish their default risk. 

The Solidity-based smart contract auditor 0x0 is another early adopter of AI, relying on automated algorithms to help with its smart contract audits. They quickly scan smart contract code to try and identify vulnerabilities and other anomalies that might create security issues. It has also created AI rug pull detectors that monitor smart contract transactions for signs that the project creators themselves might be scammers. In cases where it identifies suspect behavior, it can send out alerts and take proactive actions to protect users, such as frontrunning malicious transactions. 

Meanwhile, the well-known blockchain oracle Chainlink leverages AI to aggregate and validate real-world information from its network of decentralized data providers. The idea is to analyze all incoming data and filter out any anomalies to ensure that it only sends the most reliable information to blockchain users, increasing the accuracy of its oracle services, which have become critical to the DeFi ecosystem. 

These use cases are not exhaustive by any means, but they illustrate how AI can become central to creating smarter and more efficient DeFi applications. Just as ChatGPT changed the way we search for information and create things using our computers, these AI applications promise a similar impact in the realm of DeFi. 

How will AI transform DeFi in the future? 

One of the most exciting future applications of AI in DeFi promises to be optimized trading. The general consensus is that most traders fail to be profitable, and the very idea is often seen as gambling, with many having lost vast sums of money. 

AI might be able to turn this on its head and assist traders in achieving more positive outcomes. By analyzing user’s portfolios and behaviors, understanding their risk tolerance and studying the crypto market’s price movements, AI algorithms can provide customized trading recommendations and strategies to users. In this way, every trader will be able to make smarter trades. 

One of the projects working towards this goal is SONEX, an AI-native decentralized exchange on the Soneium blockchain that was created by Sony. It’s already seen as the flagship DEX platform on Soneium, and it’s dedicated to bridging the gap between DeFi and GameFi. 

SONEX stands out due to its integration of AI, which works to optimize each user’s trading strategy and enhance the overall user experience. One of SONEX’s novel features is the concept of Alpha Hunting, where AI agents will help users discover profitable trades and formulate comprehensive strategies to exploit those opportunities. It delivers personalized recommendations to users based on price data and market trends, aiming to provide them with an edge over the broader market.    

The promise of SONEX’s Alpha Hunting is that it can help users to find hidden opportunities buried within complex data that human users cannot spot. Using those insights, it will devise strategies that can help them to stay one step ahead of the volatile trading markets, making it an attractive offering for inexperienced traders. 

Another example of this optimized trading experience comes from Numerai, a decentralized hedge fund that uses AI to crowdsource predictions made by data scientists. These predictions are made available to the Numerai community, helping them to make better trades. 

It’s not hard to imagine a future where AI models can predict asset price movements with stunning accuracy, and the next step after this will be to automate the actual trading process, based on those insights. The advantage of AI is that, unlike humans, these algorithms never need to sleep, which means they can observe the crypto markets day and night to enter and exit trades at the most profitable moment. 

AI can also help to make decentralized applications smarter, too. Imagine a world where dApps don’t just follow predefined rules, but instead adjust themselves in a dynamic way, based on their understanding of the market conditions. Such systems will be able to understand market inefficiencies and compensate, for example by optimizing liquidity allocation and flagging possible risks. 

Furthermore, AI can help to secure DeFi protocols in future. By analyzing transaction patterns, Chainalysis can identify suspicious trades and identify potential attack vendors to help protocols defend themselves against malicious exploits. It can also help protocols to simulate possible attack scenarios and develop strategies for defending against them. 

DeFi that works for everyone

AI is well on the way towards becoming an integral part of the DeFi ecosystem, even though some challenges remain, such as the technical complexity of integrating AI algorithms and agents with blockchains, and the contrast between the transparent nature of DeFi and AI’s black box design. 

The consensus is that AI will make DeFi more accessible and make it work for everyone. By making DeFi protocols more intuitive and simplifying the complexities of creating profitable trading and yield farming strategies, it will empower users who were previously excluded. 

Still, we need to be careful. As AI becomes more powerful and integrates deeper within the DeFi ecosystem, it will be necessary to ensure fairness and protect against biases. After all, the goal is to make DeFi more accessible rather than perpetuate inequality. 

It’ll be some time before we learn the true impact of AI in DeFi, but the progress so far has been substantial. AI is enhancing DeFi’s capabilities and simplifying user experiences to create a more inviting financial system that will welcome every kind of user.