HomeKnowledge BaseHow AI agents can be used in DeFi

How AI agents can be used in DeFi

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Published Jun 20, 2025, 2:44 PM

AI agents are a game-changer. They turn the incredible power of Large Language Models (LLMs) and other AI models into autonomous programs that can work tirelessly to help you achieve your goals. Imagine having an intelligent, tireless assistant dedicated to your objectives.

Especially in the highly automated, fast-paced world of decentralized finance (DeFi), there's massive, untapped potential for AI agents to impact markets, provide unprecedented insights, and even automate complex strategies. DeFi thrives on speed, data, and efficiency, making it fertile ground for AI innovation.

Understanding how to leverage AI agents in DeFi safely and effectively opens up entirely new opportunities for market insights, sophisticated trade techniques, and enhanced security. This isn't just about automation; it's about intelligent, adaptive automation.

In this article, we’ll help you understand:

  • Understand what AI agents are at their core.

  • See practical examples of how to leverage AI agents in DeFi.

  • Learn about how CoW Protocol can help protect your AI agent's trading strategies.

This is part of our series exploring DeFi. If you’re looking to start at the beginning, check out our article: Getting Started with DeFi: Your Comprehensive Guide to Decentralized Finance - CoW DAO

Why AI agents are a good fit for DeFi

What makes AI agents uniquely suited for the DeFi landscape? It comes down to a few key characteristics of the decentralized world:

  • DeFi features many frequent, automated transactions. The very nature of DeFi protocols, with their constant swaps, liquidity provisions, and lending/borrowing actions, generates an enormous volume of data and requires rapid responses.

  • Finding meaningful trends amidst this high volume of information is incredibly difficult for humans. The sheer speed and scale of on-chain data can be overwhelming. Identifying profitable opportunities or spotting potential risks in real-time is like finding a needle in a haystack-a haystack that's constantly growing.

  • AI agents offload many of the routine analytic tasks that make understanding possible. They can tirelessly sift through blockchain data, market feeds, and news, performing the grunt work of analysis so you don't have to.

AI agents' flexibility and power are perfectly suited to the constantly shifting trends and vast data volumes inherent in DeFi analysis. They don't get tired, they don't get bored, and they can process information at speeds no human ever could.

Here's the value AI agents in DeFi can offer:

  • Accelerate analytics pipelines, delivering insights as fast as possible. In a world where milliseconds matter, AI agents provide a competitive edge by crunching numbers and delivering actionable insights with lightning speed.

  • Automate routine data processing to free up time for more valuable decision-making and development. Instead of spending hours manually tracking metrics, you can focus on refining your strategies, exploring new protocols, or innovating.

  • Give high-level insights quickly to deliver moment-to-moment market insights. Whether it's spotting an arbitrage opportunity or identifying an unusual market movement, AI agents can provide instant, distilled information.

Overview: AI agents explained

So, what exactly is an AI agent? In simple terms, AI agents are autonomous sections of a software system that process data using AI models. These AI models could be traditional Machine Learning (ML) models trained for specific tasks, or more flexible Large Language Models (LLMs) that can understand and generate human-like text.

AI agents open up possibilities for incredibly complex and powerful software architectures that fully leverage the capabilities of AI. They can operate as standalone programs, executing specific tasks independently, or, more powerfully, they can be coordinated into an agentic workflow. This is where multiple AI agents work together, each handling one specific section of the necessary processing for a larger, more complex task. You can learn more about this concept from IBM's article on agentic workflows.

Think of it like a highly specialized team: one agent might gather market data, another might analyze sentiment, a third might identify trading opportunities, and a fourth might execute the trade. Each agent performs its part, contributing to the overall goal.

Example: using AI agents for automated DeFi trading

One of the most exciting and impactful applications of AI agents in DeFi is automated trading. Here, AI agents take on the heavy lifting of complex analysis while also executing trades automatically. This creates opportunities for implementing far more sophisticated trading strategies than manual execution would allow. The process is a sort of collaboration between human strategy and AI execution, where the human sets the overarching goals and the AI tirelessly works to achieve them.

How traders interact with AI agents

It's not about turning over full control; it's about smart delegation:

  • Traders set up parameters and goals for their AI agent. This includes defining risk limits, preferred assets, profit targets, and specific market conditions they want the agent to look for.

  • The agent monitors markets continuously using these guidelines. It acts as a tireless sentinel, watching for changes 24/7.

  • It executes trades when conditions match the trader's criteria. Once the predefined rules are met, the agent can initiate transactions instantly.

  • The trader maintains oversight through dashboards and alerts. You're always in the loop, receiving notifications about trades, performance, and any unusual market activity.

  • They can adjust parameters as market conditions change. The human element remains crucial for adapting strategies in response to new information or market shifts.

Step-by-step agent automation with Ethereum

Let's walk through a simplified example of how an AI agent might automate a trading strategy on Ethereum:

Step 1 – Trader configures an AI agent with wallet permissions.

The trader securely grants the AI agent limited permissions to interact with their crypto wallet. Crucially, they set strict risk limits and trading preferences (e.g., maximum daily trade volume, assets to trade, acceptable slippage). The agent then connects to real-time Ethereum market data feeds from various decentralized exchanges (DEXs).

Step 2 – AI agent analyzes ETH price movements and volume.

The AI agent continuously processes live data. It identifies potential arbitrage opportunities (where the same asset can be bought and sold for a profit across different exchanges) or other price discrepancies across various DEXs. The agent rapidly calculates optimal trade sizes and timing based on current liquidity and gas fees.

Step 3 – When conditions align, the agent executes trades automatically.

If the market conditions meet the trader's pre-set criteria (e.g., a profitable arbitrage opportunity appears), the agent instantly executes the necessary transactions. This might involve swapping ETH for USDC on Uniswap and then simultaneously trading that USDC for more ETH on another DEX like Curve to capture the price difference. The entire process happens in milliseconds, far faster than any human could react.

DeFi use cases for AI agents

Beyond automated trading, AI agents are poised to revolutionize many other aspects of DeFi:

Research automation

AI agents can be your ultimate research assistants in the vast, ever-growing ocean of DeFi data:

  • They can tirelessly dig into market trends, analyze news reports, and even scour whitepapers for key information.

  • Using powerful language models, they can generate concise summaries of complex topics or market developments, often with extensive links to original sources for verification.

  • Through ongoing tuning and prompt engineering by human experts, these agents can become increasingly adept at producing highly accurate and relevant summaries tailored to specific research needs.

Virtual assistants

Imagine having a chatbot that truly understands DeFi and can answer your questions in real-time:

  • AI agents can power sophisticated chatbot UIs that provide instant insights into DeFi markets.

  • By accessing recent transaction logs from different chains (like Ethereum, Polygon, Solana), they can answer questions about current market trends, specific token movements, or even historical data on a particular protocol. Need to know the largest stablecoin transactions in the last hour? An AI assistant could tell you.

Automated trading

This is the cutting edge, where agents directly interact with markets:

  • These are advanced agents with secure wallet access permissions that execute transactions based on dynamic prompts and real-time market data.

  • For example, you could configure agents that trade puts and calls (options), with their actions triggered by specific trends or patterns detected in recent on-chain transactions or broader market sentiment. This allows for nuanced, algorithmic trading strategies.

Enhanced security

In a space constantly targeted by malicious actors, AI agents can provide an extra layer of defense:

  • Agents can continuously track markets for unusual behaviors, such as large, sudden movements of funds, rapid price fluctuations without clear cause, or unusual contract interactions.

  • By identifying these anomalies, they can alert users to potential ongoing attacks like rug pulls, flash loan exploits, or large-scale liquidations.

  • Working within broader market analysis and agentic workflows, these security agents can help protect your portfolio from unforeseen security risks by providing early warnings.

Yield farming and staking

Yield farming and staking pools offer high potential for asset growth, but they demand constant, rigorous trend analysis of high-volume, rapidly changing data. This includes factors like fluctuating gas fees, variable algorithmic interest rates, and pool liquidity. You can learn more about it on Hedera's DeFi yield farming page.

AI agents are ideally suited for handling these kinds of dynamic data streams and acting on broad trends in the data. They can:

  • Monitor thousands of pools simultaneously.

  • Calculate optimal entry and exit points considering gas costs and potential returns.

  • Identify the best yield opportunities across different chains based on real-time APY (Annual Percentage Yield) data.

  • Alert users to significant changes in pool conditions, helping them maximize returns and minimize impermanent loss.

How CoW Protocol helps secure AI agents in DeFi

As powerful as AI agents are, their autonomous nature can also expose them to unique vulnerabilities in the DeFi space. One of the most significant risks is Miner Extractable Value (MEV).

CoW Protocol is a meta-exchange and trading protocol designed specifically to protect users from malicious behavior in DeFi, particularly MEV attacks. You can dive deeper into this with our explainer on MEV attacks.

Agentic workflows, with their rapid and often predictable responses to market trends, can be especially vulnerable to MEV. Transaction order attacks, like front-running or sandwich attacks, can severely undercut the trends that AI agents identify and act on, eating into potential profits or even leading to losses. An AI agent might spot a perfect arbitrage, only for an MEV bot to execute its transaction just before or after, stealing the profit.

What CoW Protocol offers AI agents

CoW Protocol's innovative design offers unique advantages for AI agents operating in DeFi:

  • CoW Swap’s solver incentive architecture offers unique surplus access suited to AI agents. Instead of directly interacting with DEXs, CoW Swap uses "solvers" (third-party market makers) to find the best trade execution for users. These solvers compete to provide the best prices and are incentivized to return "surplus" value to the user. This architecture effectively undermines MEV attacks, making them unprofitable and ineffective for malicious actors, as solvers are motivated to protect user value. CoW Protocol has already protected $263 billion worth of trades from MEV. You can learn more over on CoW Swap.

  • CoW Protocol supports advanced order types and automation suitable to interfacing with agentic workflows. This means AI agents can leverage CoW Protocol's sophisticated order types, such as limit orders, allowing for more precise and automated execution strategies. The protocol is designed to be highly composable and programmable, making it an ideal interface for the complex logic of AI agentic workflows. Explore more about CoW Protocol's capabilities.

By building your AI agent strategies on top of CoW Protocol, you can ensure that your intelligent automation is not only efficient but also robustly protected against the hidden dangers of the DeFi market.

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