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DeFAI: AI-driven DeFi innovation unleashing the potential of Decentralized Finance
DeFAI: How Artificial Intelligence Unleashes the Potential of Decentralized Finance
Decentralized Finance ( DeFi ) has been an important pillar of the crypto ecosystem since its rapid development in 2020. Although innovative protocols have emerged one after another, the complexity and fragmentation of DeFi have also increased, making it difficult for even experienced users to navigate the numerous blockchains, assets, and protocols.
At the same time, artificial intelligence ( AI ) has evolved from a broad foundational narrative in 2023 to a more specialized, agent-oriented focus in 2024. This shift has given rise to DeFi AI ( DeFAI )—a burgeoning field that enhances DeFi through automation, risk management, and capital optimization.
DeFAI spans multiple layers. The blockchain serves as the foundational layer, while AI agents need to interact with specific chains to execute transactions and smart contracts. The data layer and computation layer provide the necessary infrastructure for training AI models, which are derived from historical price data, market sentiment, and on-chain analysis. The privacy and verifiability layer ensures that sensitive financial data remains secure while maintaining trustless execution. Finally, the agent framework allows developers to build specialized AI-driven applications, such as autonomous trading bots, credit risk assessors, and on-chain governance optimizers.
As the DeFAI ecosystem continues to expand, the most prominent projects can be divided into three main categories:
1. Abstraction Layer
These types of protocols serve as user-friendly interfaces for DeFi, allowing users to input prompts that are executed on-chain. They are often integrated with multiple chains and dApps and execute user intentions while simplifying manual steps in complex transactions.
Some functions that these protocols can execute include:
The abstract layer protocol allows for complex cross-chain operations to be completed in just one step, greatly simplifying the user experience.
2. Autonomous Trading Agent
Unlike traditional trading bots that follow preset rules, autonomous trading agents can learn and adapt to market conditions, adjusting their strategies based on new information. These agents can:
3. AI-Driven DApps
DeFi dApp provides functions such as lending, swapping, and yield farming. AI and AI agents can enhance these services in the following ways:
These categories of protocols have been well received by the market. However, to provide better products and optimal results, they should consider integrating various datasets of different quality to elevate their products to a new level.
Data Layer - Powering DeFAI Intelligence
The effectiveness of AI depends on the data it relies on. To enable AI agents to work effectively in DeFAI, they require real-time, structured, and verifiable data. For example, the abstraction layer needs to access on-chain data through RPC and social network APIs, while trading and yield optimization agents need data to further refine their trading strategies and reallocate resources.
High-quality datasets enable agents to better predict future price behavior, providing trading recommendations to suit their long or short position preferences for certain assets.
The main data providers of DeFAI include:
These data providers offer rich data resources for AI agents, supporting them in making more accurate predictions and decisions.
Development of AI Agent Blockchain
In addition to building a data layer for AI and agents, some blockchains are positioning themselves as full-stack solutions for DeFAI. The Mode network recently deployed Mode Terminal, which is a co-pilot for DeFAI used to execute on-chain transactions through user prompts. Mode also supports many AI and agent-based teams, integrating multiple AI protocols into its ecosystem.
Other mainstream blockchains such as Solana, Base, and NEAR are also actively laying out plans in the AI agent field, launching various incentive programs and funds to support the development of AI agents.
The Future Development of DeFAI
Currently, most AI agents in DeFi still face some limitations in achieving full autonomy. The next phase of DeFAI may focus on integrating useful data layers to develop the optimal agent platform or agents. This will require deep on-chain data, synthetic data, and market sentiment analysis, among other things.
The ultimate goal is for AI agents to seamlessly generate and execute trading strategies from a single interface. As these systems mature, future DeFi traders may rely on AI agents to autonomously assess, predict, and execute financial strategies with minimal human intervention.
Despite certain pullbacks in AI agent tokens and frameworks, DeFAI is still in its early stages, and the potential of AI agents to enhance the usability and performance of DeFi cannot be overlooked. The key to unlocking this potential lies in acquiring high-quality real-time data, which will improve AI-driven trading predictions and execution.
In the future, verifiability and privacy will become key challenges that protocols must address. Integrating technologies based on TEE, FHE, and even zero-knowledge proofs can enhance the verifiability of AI agent behaviors, thereby achieving trust in autonomy.
Only by successfully combining high-quality data, robust models, and transparent decision-making processes can DeFAI agents achieve widespread application and truly unleash the potential of Decentralized Finance.
![DeFAI Overview: How AI Unlocks the Potential of Decentralized Finance?](https://img-cdn.gateio.im/webp-social/moments-56a89e79609d8f982d5d31dadfad9205.webp01