In This Article
AI agents based on artificial intelligence (AI) are intelligent tools that simplify cryptocurrency trading and management of decentralized platforms.
In the crypto community, there is increasing talk about these mysterious AI agents.
AI Agents: What Are They?
In short, AI agents are super-smart assistants that can significantly simplify the process of trading cryptocurrencies. They operate on artificial intelligence, allowing them to solve various tasks in the blockchain extremely quickly. These agents make decisions and take necessary actions without direct user involvement.
AI agents are similar to applications that know the user exceptionally well. They observe, think, and act without waiting for you to click the right button.
For example, think of your favorite music streaming app that creates playlists based on your interests. AI agents work in a similar way.
The use of this innovative AI-based tool is rapidly gaining popularity among users. According to a Salesforce study, 39% of users are open to having AI agents schedule meetings for them. Furthermore, 32% of Generation Z members want these agents to compile shopping carts and place orders on their behalf.
However, to use AI agents effectively, it’s important to first understand how they work.
How AI Agents Work
As mentioned earlier, AI agents automate tasks in the blockchain. They gather data, analyze it using artificial intelligence, and then make decisions automatically.
AI agents are highly multitasking. Imagine you have hired an assistant who monitors all the trends in the crypto market, knows the best moments to invest, and can do this faster than you can update your portfolio.
All you need to do is sit back and let the AI agent get to work.
Stages of AI Agent Operation
The operation of AI agents consists of three stages:
- Information Gathering. First, AI agents collect data: market trends, blockchain transactions, DeFi statistics, and much more.
- Decision Making. Next, they analyze the gathered data using programmed information, advanced machine learning, and predictive analytics. Based on the analyzed data, AI agents then make decisions about the best course of action. This process is similar to a GPS system calculating the fastest route to a specific destination.
- Action Execution. Finally, AI agents take actions, such as placing trades, moving funds, or executing smart contracts.
In many ways, AI agents are similar to the AI bots we are already familiar with. However, they are significantly more advanced.
What AI Agents Are Made Of
The technology behind AI agents is built on several interconnected components. Here are the main ones:
- Learning Model. This is the brain of the agent. It collects and processes blockchain data.
- Decision-Making Mechanism. This can be considered the agent's personal strategist, allowing it to analyze processed data and make decisions about the best and most justified actions.
- Action Module. This executes the agent's decisions, whether it's placing a trade, moving funds between wallets, or executing a smart contract.
- Communication Interface. This component enables AI agents to interact with users and other systems. The communication interface handles status updates, notifications, and task confirmations. For example, through this interface, an AI agent can send you a notification about the completion of a trade or the movement of assets into a high-yield pool.
- Security System. In the blockchain space, security is the most critical component. This system protects user data, private keys, and transaction details.
- Blockchain Integration Level. This module connects the AI agent to networks, allowing it to interact with smart contracts, wallets, and decentralized applications (dApps). It ensures the agent operates across various ecosystems, whether it's Ethereum, Solana, or Base.
- Autonomous Execution Level. The uniqueness of AI agents lies in their autonomy. This component ensures that the agent can operate independently, monitoring all necessary conditions and executing actions without constant user intervention.
How AI Agents Differ from Traditional AI Projects
AI agents can easily be confused with cryptocurrency projects based on artificial intelligence. However, there are key differences between them.
Traditional AI projects are broader initiatives that integrate neural networks into blockchain technology. Their main goal is to enhance specific aspects of the cryptocurrency ecosystem, such as improving transaction efficiency, providing analytics, creating smart contracts, and much more.
AI projects often develop platforms or tools that use artificial intelligence to create new functionalities.
Cryptocurrency AI agents are autonomous entities. They perform specific tasks without human involvement, such as trading, analyzing data, or creating content.
| Aspect | Cryptocurrency AI Projects | Cryptocurrency AI Agents |
|---|---|---|
| Field of Activity | Integration of artificial intelligence to enhance blockchain functionalities. | Specialized autonomous entities that perform specific tasks within the crypto ecosystem. |
| Functionality | Development of tools and infrastructure for applying AI in cryptocurrency operations. | Autonomous execution of specific tasks, such as trading, analysis, or content creation. |
| Examples | Fetch.ai (FET), SingularityNET (AGIX), Ocean Protocol (OCEAN). | Virtuals Protocol, AIxbt, Truth Terminal.ShareRewrite |
❗ Interesting fact! Some AI agents actively issue their own tokens to encourage user engagement. For example, the Virtuals Protocol project recently introduced its coin — VIRTUAL. With these assets, community members can participate in platform governance and gain access to certain premium features.
Challenges in Working with AI Agents
AI agents may seem like the perfect solution for any crypto enthusiast. However, these autonomous tools are not without their flaws. Let's explore the main challenges that this new technology is already facing.
Integration Complexity with Blockchain
Integrating cryptocurrency AI agents into blockchain networks like Ethereum or Solana can become a logistical nightmare. Different protocols and decentralized infrastructures require cutting-edge solutions, which can complicate interactions between autonomous tools and blockchain ecosystems.
Data Reliability
AI agents make decisions based on real-time data. However, data on the blockchain is not always the most reliable. Therefore, a primary task for these tools is to filter out potential "pitfalls" when working with oracles that gather external information and smart contracts that may be prone to inaccuracies.
Security Risks
The autonomous operation of AI agents makes them targets for cyberattacks. Hackers can exploit vulnerabilities in smart contracts to gain access to private keys. Additionally, they can manipulate market trends to deceive the agent.
Scalability Issues
Blockchains often face congestion, leading to transaction delays and increased fees. This can hinder the performance of AI agents that need to act quickly.
Regulatory Uncertainties
Regulation remains a fundamental and ongoing challenge for the crypto market. Regulatory frameworks concerning blockchain and AI are constantly evolving. Autonomous tools may raise questions about liability, especially when involved in financial transactions.
Ethical Considerations
Granting AI agents significant freedom in their actions can lead to unforeseen consequences. If an agent executes a trade that destabilizes the market, who will be held accountable?
All of these challenges may seem complex and daunting. However, they are surmountable.
The Future of AI Agents
The future of AI agents looks promising, especially as more blockchains integrate AI-based Web3 automation into their ecosystems.
Over time, we are likely to see increasingly advanced autonomous tools capable of managing complex DeFi strategies emerging in the market. However, the issues outlined above will persist for now. In many ways, these challenges will define the adoption curve of AI agents.
