In This Article
Decentralized finance lacks simplicity. People outside of Web3 find it difficult to interact with DeFi protocols and deal with liquidity, returns from staking and complex trading strategies.
To simplify novice interaction and enhance the crypto-financier experience, developers turned to AI. This is how the DeFAI narrative emerged.
Coinpaper talks about the symbiosis of current AI and DeFi trends, analyzes new features of financial applications and their impact on users and the industry.
Why Use DeFai in Applications?
Decentralized finance in its current form has the potential to become a worthy alternative to the current financial system and take a place in the international economy. One of the problems of mass adoption of cryptocurrencies and DeFi remains the complexity of the technology. The integration of AI into DeFi, known as DeFAI, is still in its early stages. As this technology develops, its definitions and applications will continue to evolve.
Many users, accustomed to the intuitive interface of modern applications, do not want to delve into the intricacies of blockchain protocols and understand the structure of decentralized finance. So how can they benefit from DeFi? Developers have attempted to answer this question by introducing network abstraction technology, incorporating the more common one, account abstraction.
By enlisting the help of AI, creators of financial dapps are implementing simplifications in an effort to lower the user experience (UX) threshold as much as possible. This approach has become an element of a new narrative, DeFAI (DeFi + AI). The symbiosis aims to remove obstacles by offering a simple, custom interface for working with decentralized applications. The future of DeFAI holds the promise of evolving personalized financial solutions and user-driven innovations that cater to a broader audience within the DeFi space.
For advanced crypto-financiers, DeFAI offers an improved user interface (UI) and increased profits through the use of sophisticated trading strategies and onchain analytics. Simple automation marks the beginning of a transformative shift towards more sophisticated AI-driven strategies, paving the way for increased reliance on machine intelligence within the DeFi space.
Pairing with AI has allowed several features to be added to the dapps:
risk management - identifying potential threat of loss of profit or capital and minimizing the consequences;
automated trading. Algorithms analyze market patterns and execute trades independently;
fraud prevention through smart detection systems;
optimizing profitability. Strategies seek to maximize profits by interacting with multiple protocols and selecting the most profitable ones.
AI dapps have created a niche and occupied it
The bulk of dapps in the DeFAI category are AI agents. The sector of such bots has noticeably slowed down since the boom of late 2024. And while the Binance exchange attempted to draw attention to them in early February 2025, that didn’t help the tokens of popular projects recover from the scale collapse. The market cap of the DeFAI category has also been affected by these trends.
On March 18, former platform head Changpeng Zhao called for AI developers to focus on creating useful products rather than engaging in tokenization.
According to CryptoRank, the DeFAI narrative has been gaining momentum since January 2025. The chart below shows a 62.6% increase in subcategory value over a 30-day period. Among the leaders were tokens of related areas: AI-agents, portfolio managers and trading strategy platforms. Crypto investors are increasingly attracted to projects that showcase strong market potential, reflecting a bullish trend in the cryptocurrency sector.
The emergence of AI agents with the ability to autonomously process transactions on the blockchain like Griffain and Orbit has contributed to the DeFAI trend.
On March 17, 2025, crypto analyst Miles Deutscher identified the significance of the DeFAI sector in the long term. He emphasized users’ commitment to the two leading categories over the past 90 days. He chose a favorite, the ANON token of the Hey Anon project, to invest in the new direction.
AI assistants have quickly become popular due to automated features that simplify interactions with DeFi protocols. For example, Griffain-based agents can be created for token launching, SOL staking, and liquidity management, enhancing the defi experience for users.
The advances are made possible by the implementation of Trusted Execution Environments (TEE). The Phala Network protocol implements the technology and enables the deployment of custom AI agents on its base. TEE enables operations in a secure and confidential environment, protecting sensitive data from malicious attacks, improving efficiency and reliability of operations.
Despite bearish sentiment in the market, cryptocurrency experts at Sygnum Bank gave a positive forecast for AI assistant tokens in 2025. However, they remain predominantly speculative assets at the current point in the cycle.
How DeFAI applications are structured in decentralized finance
AU-based systems or intent-based blockchains also serve to simplify UX. In the former, users express a desired outcome and the system, often with the help of solvers, finds the best way to achieve it; DeFAI applications can be tailored to individual preferences, providing personalized financial solutions.
For example, when exchanging tokens or transferring assets between networks, a solver determines the best route in blockchain technology, taking into account gas fees, slippage, and liquidity, and then executes the necessary transactions.
In the case of DeFAI, machine learning algorithms, artificial intelligence and large language models (LLMs) are used to facilitate interaction with the blockchain. Instead of focusing on the infrastructure required to execute intent, artificial intelligence makes more informed decisions before transactions are executed.
Artificial intelligence agents analyze onchain data, predict market trends, and recommend actions that align with the user’s goals. For example, selecting the optimal pool to provide liquidity or optimizing asset allocation for yield optimization.
AI improves DeFi tools. Among the available dapps are the following innovations:
Personalized financial strategies. The AI generates conclusions based on the provided data on transaction history, investment patterns and risk management. Subsequently, DeFAI applications create customized financial strategies. For example, analyzing onchain activity to highlight frequent interactions with stablecoins and then recommending high-yield platforms to stack them;
target trading. Watching short-term price fluctuations often leads to impulsive decisions. DeFAI applications help automate trading strategies, reducing the emotional impact. Users can set clear financial goals, such as: “Sell 30% of ETH if the price falls below $1800 to minimize losses, or sell at the $2500 level to lock in a profit.”
choice of validator for staking. Incorrect pruver selection when there are a large number of them can result in reduced awards or even penalties. DeFAI applications analyze the sample by evaluating activity time and reputation metrics;
text-based portfolio management. Thanks to chatbot interfaces, DeFAI dapps allow portfolio management in the form of correspondence. Some dapps integrate with messengers Telegram and Discord.
AI algorithms and DeFAI agents power these DeFAI applications, enhancing decision-making and efficiency through real-time data analysis and personalized services. However, challenges related to transparency, data privacy, and the complexity of these algorithms raise concerns about accountability and bias.
DeFAI is in business
As of March 20, 2025, the market capitalization of the DeFAI category in CoinGecko approached $900,000. DeFAI technology empowers businesses to operate more efficiently by reducing costs and enhancing operational capabilities.
Market analysis agents, trading decision assistants, infrastructure platforms for programming trading strategies and automated investment systems are among the submitted projects, providing valuable insights for making informed financial decisions in DeFAI.
First place goes to PAAL AI - a multi-functional AI platform in the form of a chatbot.
Next is the popular AI agent Aixbt. This autonomous assistant is released on the Virtuals Protocol platform on the Base network. It allows you to perform fundamental analysis of cryptocurrencies, track social media sentiment, and build a dynamic picture of the market in real time.
The third place is occupied by ChainGPT -a startup in the field of automated trading, creation of smart contracts and NFT.
The infrastructure solutions sphere is represented by RSS3, an information gathering project and AI agent launch pad.
The fifth place by capitalization is occupied by the brainchild of experienced DeFi developer Daniel Sesta - Hey Anon. Dapp collects information about projects on different blockchains and “communicates” with the user through a dialog box. The application helps to make an informed decision and fine-tune trading algorithms using stop-losses of different complexity.
Investment managers’ DeFAI systems are designed to help with portfolio management:
Aspis. The AIDAO framework allows AI agents to be customized to serve vaults and dynamic fund parameters;
Mozaic Finance. AII managed income farming platform with interoperability optimizes return strategies and performs automatic reinvestment;
Almanak. With DeFi analytics and forecasting, optimizes trading strategies and automatically rebalances investment portfolio assets.
Hallucinations instead of conclusions in AI algorithms
One thing to consider is that AI agents are prone to “hallucinations“ when LLMs produce nonsensical or incorrect answers. Imagine a “seizure” occurs during a token exchange. The agent overstates the commission or transfers assets to the wrong contract address, resulting in financial losses. Ensuring robust security measures is crucial to prevent such financial losses.
AI models are potentially susceptible to hacking. In the context of DeFi, this could result in the loss of user funds. The mass application of AI agents in decentralized finance increases the risk of systemic failure across the entire cryptocurrency market. AI can make systems more reliable by identifying risks and optimizing decision-making processes.
The DeFi + AI synthesis provides an opportunity to rethink the relationship between autonomy and automation. Unlike intent-based network abstraction protocols, DeFAI preserves human participation by acting as an advisor rather than an executor. Protecting sensitive information is essential to ensure data privacy and security in these systems.
The potential of AI agents at DeFi is just beginning to be realized. The very fact that they are always on and can independently execute an infinite number of transactions in milliseconds gives them a competitive advantage. But as with any new technology, the consequences of AI agents are not always predictable, and users should always weigh the risks involved.
