Crypto AI agents are autonomous software programs that use artificial intelligence to analyze, decide, and execute blockchain-related tasks without human input.
Crypto AI agents are autonomous tools that can trade, manage portfolios, and interact with blockchains without human input.
AI agents adapt and learn, unlike bots that follow rigid rules, enabling more intelligent decision-making.
AI agents can power viral crypto narratives, as seen in projects like Truth Terminal and GOAT
Platforms like Virtuals Protocol let anyone build and own AI agents on-chain, fueling a new wave of decentralized applications.
Use with caution: While powerful, AI agents can make inaccurate predictions — always verify data and do your own research.
This article was updated in April 2025 by Vera Lim.
Imagine having a digital assistant that can analyze market movements, manage your crypto assets, and even manage your social media for you. That’s what crypto AI agents are. They are autonomous AI-powered programs, designed to make decisions and carry out actions in the crypto world with little to no human intervention. They simplify and optimize blockchain interactions, abstracting away the complexities.
“I think we’re going to live in a world where there are going to be hundreds of millions or billions of different AI agents. Eventually, probably, more AI agents than there are people in the world.”
— Mark Zuckerberg | CEO, Meta
Crypto AI agents can learn and adapt to market information. This makes them particularly suited to performing tasks on the blockchain, including trading, portfolio management, or even posting market updates on social media. In fact, in a recent CoinGecko survey, more respondents trusted AI agent key opinion leaders (KOLs) on Crypto Twitter than human KOLs.
AI agents are particularly suitable for crypto, as the crypto space is decentralized and data-heavy with blockchain information publicly available. Crypto is also volatile, where users may need to split-second decisions based on market happenings. AI agents in crypto can be used for tasks ranging from trading, portfolio management, blockchain governance, and even as KOLs as mentioned above.
AI agents can spark hype online by engaging with communities and by having a unique story that captures attention. The story of Truth Terminal and GOAT sums it up.
The AI agent narrative in crypto began with a project called “Truth Terminal.” Truth Terminal created a satirical meme-based religion, and as it was designed to operate semi-autonomously on X, it started posting about its “Goatse Gospel.”
In July 2024, Truth Terminal gained significant attention when Marc Andreessen, co-founder of a16z, became intrigued by its posts. He ended up sending $50,000 in Bitcoin to a wallet address provided by Truth Terminal, marking one of the first instances of a significant financial contribution from a human to an AI agent in the crypto space.
Truth Terminal eventually spawned a memecoin, GOAT, through Pump.fun on Solana. The token took off, reaching a peak of over $1.2 billion in market cap and Truth Terminal became the first AI agent millionaire.
Crypto AI agents usually use a conversational interface, like a chatbot, where users can enter their questions. Once it understands the context of the user’s question, it gets to work.
Collect Data: The AI agent starts gathering information from blockchains like transaction details, and from sources ranging from social media, news sites, and price feeds.
Analyze and Learn: Using machine learning models, agents search for patterns and trends. For example, an agent might notice when a token is suddenly surging in popularity on social media.
Make a Decision: Based on their analysis, the agent decides on the next course of action based on its design. This could be placing a trade, staking the token, or posting its analysis online.
Take Action on the Blockchain: The agent then executes its plan, like selecting the decentralized exchange (DEX) with highest liquidity to buy a token, or choosing a validator to stake tokens with. It also ensures that transactions are executed correctly on the blockchain.
Use cases for AI agents include:
Market intelligence
Market Research
Customer support
Automated trading
Portfolio management
DeFi strategy
Fraud detection
The most common use case for AI agents in crypto are market updates and automated research for due diligence. These agents automate the process of tracking and interpreting market trends, offering real-time insights.
aixbt is an example of a crypto AI agent that provides crypto market intelligence. Users will need to hold AIXBT tokens in order to access the terminal, which offers momentum graphs and other insights to help their users identify up and coming narratives. It also posts market updates on X.
Another common use case for AI agents is customer support, where they take on the role of support teams, delivering personalized customer interactions.
Sensay, a platform designed for creating custom AI agents, enables businesses to provide 24/7 support.
Would you trust an AI to trade crypto for you? Proponents believe that AI agents are not subject to emotional trading, allowing users to avoid situations like FOMO and panic-selling. Based on a survey by CoinGecko, 1 in 2 people think that AI agents will be better at crypto trading and investing than humans. In fact, 87% of respondents were willing to let AI agents manage at least a tenth of their crypto portfolio.
While using crypto AI agents for trading is still in its early stages, PAAL AI’s SwingX Agent is live and Wayfinder is available for select users. Users will require paid access for advanced features.
AI agents can simplify DeFi interactions, executing swaps, bridging assets, and even manage automated strategies.
HeyAnon is tailored for DeFi, allowing users to specify assets, amounts, conditions, and triggers for a transaction. It can also be used for information mining.
AI agents are already being used in traditional finance for fraud detection and cybersecurity. These are used to scan real-time financial transactions, detect anomalies, and prevent fraudulent activities.
That said, there has yet to be any definitive AI agent project designed for fraud detection within the decentralized crypto space.
AI agents in crypto offer users three key benefits:
Autonomous Decision Making
Efficiency
24/7 Operation
AI agents can analyze large volumes of data across the blockchain, social sentiments, and even market trends in real-time. This enables them to make faster data-driven decisions than a human would.
They can also tailor strategies based on a user’s preferences, risk profile, and on-chain behavior. Also, humans are subject to more emotional trading, where they may panic-sell or FOMO-buy, while an AI agent only makes decisions based on data.
Crypto AI agents can quickly sift through all the noise and review vast amounts of data, from token price changes to social media mentions, providing users with distilled information they can use to make more informed decisions.
AI agents can also automate manual operational tasks, like bridging tokens across blockchains, swapping, staking, and borrowing.
Crypto markets never sleep, and neither do AI agents. This means that crypto AI agents can react to market changes all the time, monitoring opportunities, executing trades, or flagging risks.
While AI agents can improve efficiency and provide insights, there some risks associated with them include:
Inaccurate Predictions
Market Manipulation
Overdependence
Security Concerns
AI agents can be wrong if they lack full context or if the data they reference is outdated, incomplete, or incorrect. AI agents may also be unable to accurately address complex questions, like the impact of regulatory changes to a specific cryptocurrency.
To avoid this, you can continue to do their own research and verify statements made by the AI agent. Alternatively, asking the AI agent for its sources, and how it arrived at its conclusion, may also provide further insights.
There is a risk of market manipulation if many AI agents hype up the same token, collectively driving up prices, which may subsequently result in a crash.
As always, you should do your own research on any tokens before investing, while being careful of falling prey to FOMO.
While AI agents can simplify the research process, it is also easy to become overdependent on AI agents. This may result in users not verifying information from the AI, or considering insights from other sources.
Crypto AI agents should be used as a tool for additional insights instead of the sole advisor, while you continue doing your own research before undertaking any large trades or investments. In cases where the AI agent is trusted to manage the portfolio, you can set limits like requiring manual approval for large trades.
If you intend to use a crypto AI agent for portfolio management and it has direct access to your funds, there is the risk of cyberattacks that can compromise your accounts and assets.
When choosing a crypto AI agent, select one with a good track record of cybersecurity, which has undergone security audits that cover its smart contracts and DeFi security. You may also wish to add manual approvals for large trades based on your risk tolerance.
Crypto AI agents can be easily confused with bots because, like bots, they too automate tasks, reply to queries, and assist the user in menial tasks. However, they are very different.
The difference between bots and AI agents can be boiled down to their deterministic and probabilistic nature, respectively.
Bots are deterministic. This means, they follow predefined rules and scripts created by developers, executing tasks exactly as instructed. For example, a trading bot might execute a buy order when a token price drops below a certain threshold, without any ability to assess whether this action is contextually appropriate.
Crypto AI agents are probabilistic. They use machine learning and AI models to analyze data, predict outcomes, and make decisions. Instead of rigid rules, they adapt based on patterns, trends, and probabilities, allowing for more nuanced and intelligent actions.
Bots
AI Agents
Decision-making
Rigid and rule-based
Flexible and adaptive
Adaptability
Limited
High
Risk Management
Technical indicators
Real-time data
Task complexity
Low and repetitive (deterministic)
High and dynamic (probabilistic)
Automation Level
Stop-loss or take-profit orders
Predictive analytics and hedging
Example
Arbitrage bots, market makers
Sentiment analysts, portfolio managers
These tokens are listed in order of market cap on CoinGecko. Most of these are infrastructure projects, focused on building AI models and autonomous agents, instead of consumer projects.
The Artificial Superintelligence Alliance is a decentralized AI consortium founded by Fetch.ai, SingularityNET, and Ocean Protocol, with CUDOS as a network member. It aims to be the largest open-source and decentralized entity in the field of AI research and development, providing its extensive developer community with tools for AI.
FET tokens can be used to secure the Fetch.ai mainnet through staking, register and interact with AI agents in the ecosystem, and access AI tools, datasets and compute resources.
At time of writing, FET has a market cap of over $1.2 billion.
Virtuals Protocol is built on Base (Coinbase’s L2). It allows users to create, own, and deploy AI agents. Virtuals turns AI agents into tokenized assets, where tokens grant users fractional ownership. This allows users to own a piece of an AI agent and profit from its success.
VIRTUAL tokens are needed to create new agents, and these tokens are used to establish the agent’s liquidity pool. Transactions are routed through the VIRTUAL token, where other cryptocurrencies must be swapped to VIRTUAL before purchasing any agent tokens. VIRTUAL is also used to pay for AI agent inferences on a per-use basis.
At time of writing, VIRTUAL has a market cap of around $357 million.
OriginTrail tackles misinformation by enhancing discoverability and ensuring information authenticity. It uses the decentralized knowledge graph to present a global open data structure of interconnected Knowledge Assets hosted on an open, decentralized network of nodes.
TRAC tokens can be used for delegated staking to enhance the security of Core Nodes on OriginTrail.
At time of writing, TRAC has a market cap of around $188 million.
Ai16z, now known as elizaOS, began as an experiment where AI agents autonomously managed crypto assets for a DAO on-chain, with the idea that an AI investment agent might outperform venture investors. As elizaOS, it is a framework designed to create, deploy, and manage autonomous AI agents. On a side note, the DAO is still active, with $25M in assets under management (AUM).
The AI16Z token is used mainly for governance, and serves as the only way for users to gain exposure to elizaOS and the DAO.
At time of writing, AI16Z has a market cap of around $150 million.
Freysa is the world’s first evolving Sovereign Agent, which is an agent where humans do not retain control of the agent’s private keys or memory, and which functions without human oversight.
While the FAI token is live, the utility of the token is still in development.
At time of writing, FAI has a market cap of around $124 million.
PAAL AI is focused on creating user-friendly products using AI technologies like Natural Language processing, machine learning, and automation. One of its products is Paal X, an agent designed to identify and trade profitable trading opportunities in the crypto market.
According to the project, PAAL offers revenue sharing, staking rewards, and access to exclusive AI services.
At time of writing, PAAL has a market cap of over $118 million.
Looking to build your own AI agent? Here are some platforms you can check out.
Virtuals Protocol is a blockchain-based platform built on Base (Coinbase’s L2) that allows users to create, own, and deploy AI agents. Tokenization is a core component of how Virtuals Protocol works. It turns AI agents into tokenized assets and enables fractional ownership. As a result, users can own a piece of an AI agent and potentially profit from its success.
Virtuals Protocol’s AI agents are designed to be multimodal, meaning they can interact through text, speech, and 3D animations. They can perform tasks like picking up items in games or engaging with users on platforms like TikTok or Telegram. The G.A.M.E (Generative Autonomous Multimodal Entities) framework supports this by allowing seamless integration of AI agents into consumer applications.
The protocol has also been competing very closely with Bittensor, the reigning champion of the crypto AI narrative. In late November of 2024, Virtuals Protocol overtook Bittensor in mindshare before TAO reclaimed its position about a week later.
Luna (a livestreaming AI agent with a large following on TikTok) and Sekoia (an on-chain venture capitalist agent) are examples of AI agents on Virtuals Protocol.
“Based Agents,” introduced by Coinbase, are AI agents that are built on the Base blockchain. Base is a Layer 2 blockchain developed by Coinbase that aims to provide a secure, low-cost, and developer-friendly platform for building decentralized applications, including AI agents.
Based Agent is a tool that enables users to create AI agents capable of handling on-chain activities. With this no-code tool, users can set up an AI agent in under three minutes (according to Coinbase) to perform tasks such as trades, swaps, and staking. The setup requires an API key from Coinbase’s developer program and one from OpenAI, along with forking a Replit template.
What makes Based Agents special is that they are crypto-native. These agents are designed to interact directly with blockchain networks and decentralized applications. They can hold and manage cryptocurrencies, execute trades, interact with smart contracts, etc. The cherry on top is the ready-to-use template that Coinbase provides.
The AI agent narrative is very new and, understandably, carries additional risk. On the bright side, this could be a lasting and revolutionary narrative that assists the web3-uninitiated and fuels adoption by emulating human-like interactions.
From an investment perspective, while AI agents can be powerful tools for navigating the crypto market, over-reliance on them can be detrimental. Investors risk becoming complacent, neglecting their own research and critical thinking.
Always do your own research before engaging in any crypto investment or trading strategy.
At time of writing, the best 3 AI agent tokens by market cap are:
Artificial Superintelligence Alliance (FET)
Virtuals Protocol (VIRTUAL)
OriginTrail (TRAC)
You can buy crypto AI agents tokens through centralized exchanges like Binance, Bitget, LBank, or OKX. However, centralized exchanges may not have newer tokens like HeyAnon. In these cases, you can purchase them through a DEX like Raydium. For tokens created with Virtuals, you can buy them directly through the protocol.
Crypto AI agents are generally safe to interact with, especially on established social platforms, as long as users do not share personal information like wallet seed phrases, passwords, social security numbers, and other ID numbers or identification details.
Here’s a safety checklist when using AI agents:
Never share your seed phrase with AI agents.
Use manual approvals for large trades.
Check for smart contract audits.
Using AI for crypto trading is still in its early stages. However, Paal X has a model that lets users auto-trade calls generated by the model, although it requires a paid subscription.
Crypto AI Agents: What They Are, How They Work, and Top Tokens to Watch – CoinGecko
