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- AI agents have the potential to generate economic value of almost $2.9 trillion by 2030 in the United States. (<\/span>Source<\/span><\/a>)\u00a0\u00a0\u00a0<\/span><\/li>\n
- A survey by LangChain in 2024 found that around 51% of professionals used AI agents in production with 78% actively planning to implement them soon. (<\/span>Source<\/span><\/a>)<\/span><\/li>\n<\/ul>\n
Agentic AI can bring immense value to the table, and professionals have been acknowledging its potential for few years now. AI agents offer more than generic automation and transform LLMs into smart autonomous entities that can perceive the environment, implement reasoning, and execute actions to achieve their goals. Learning how AI agents can complement blockchain and web3 technologies will help you understand the foundations of autonomous web3<\/a> and blockchain systems.\u00a0<\/span><\/p>\n
Understanding the Definition of AI Agents in Web3 Contexts\u00a0<\/b><\/h2>\n
The best way to understand how AI agents can influence web3 involves discovering how they are different from traditional bots. Traditional web bots rely on rigid and hardcoded logic, which means that they execute predefined actions when specific conditions are met.\u00a0<\/span><\/p>\n
On the contrary, AI agents have the capability to build autonomous blockchain systems as agents use large language models<\/a> and machine learning frameworks. With these technologies, agentic systems have the capabilities for reasoning, planning, and adapting to diverse environments.<\/p>\n
If you bring AI agents into the domain of blockchain networks, the agents will take on some of the native properties of web3.<\/span><\/p>\n
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- AI agents can become self-sovereign entities capable of owning private keys and crypto assets and managing their balance sheets without human intervention.<\/span><\/li>\n
- The use of agentic AI in web3 will empower agents to interact with decentralized applications<\/a> and smart contracts without depending on centralized intermediaries.<\/span><\/li>\n
- The actions, financial transactions, and logic parameters of AI agents can be documented transparently on immutable decentralized ledgers.<\/span><\/li>\n<\/ul>\n
You can notice that web3 complements the limitations of AI agents by providing a native on-chain identity through public keys. AI agents also leverage web3 to gain access to a financial rail in the form of cryptocurrency for autonomous global transactions.<\/span><\/p>\n
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The relationship between AI agents and web3 is purely symbiotic with both of them filling up the limitations of the other. AI agents bring cognitive capabilities while blockchain and web3 offer secure economic rails and sandbox environments.<\/span><\/p>\n
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Contributions of Web3 to AI Agents<\/b><\/h4>\n<\/li>\n<\/ul>\n
The potential of AI agents is extremely limited in the web 2.0 landscape. You cannot have AI agents opening a bank account or signing legal contracts without human intervention in web 2.0. Web3 can solve this problem by providing identities to AI agents and empowering them to pay for its compute resources. AI agents in the domain of web3 can also charge users for their services and raise capital to invest in decentralized ecosystems.<\/span><\/p>\n
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Contributions of AI Agents in Web3<\/b><\/h4>\n<\/li>\n<\/ul>\n
The utility of AI agents in blockchain revolves around making web3 accessible to everyone. You may have noticed how web3 environments can be extremely complex and difficult to navigate for everyday users. The example of DeFi<\/a> can help you understand how AI agents can revolutionize the web3 experience for users. DeFi users have to monitor gas fees, yield farms, slippage, and liquidity pools across multiple chains, which introduces complexities. AI agents can remove this complexity by translating goals specified by DeFi users into multistep workflows.<\/p>\n
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<\/a><\/p>\nIdentifying the Core Use Cases of AI Agents in Web3\u00a0<\/b><\/h3>\n
You can gauge the impact of AI agents on the process of building purely autonomous web3 and blockchain systems through use cases of agentic AI. The combination of AI agents and web3 will lead to significant disruption across decentralized finance, digital culture, and governance.\u00a0<\/span><\/p>\n
1. Autonomous DeFi\u00a0<\/b><\/h4>\n
Conventional algorithmic trading bots leverage historical data and predefined mathematical parameters to execute trades. On the contrary, AI agents can conduct real-time sentiment analysis on social media data and read governance proposals of DeFi protocols<\/a>. Agentic systems are also capable of monitoring on-chain liquidity changes and facilitating dynamic adjustment of portfolios.\u00a0<\/span><\/p>\n
AI agents can also serve as powerful tools for managing your yield farming portfolio across different protocols. You will also notice applications of AI agents in DeFi helping with automatic fund transfers to maximize returns. Most important of all, AI agents are always operational and can make complex trading decisions faster than human traders.<\/span><\/p>\n
2. On-Chain AI Influencers<\/b><\/h4>\n
The demand to build web3 AI agents that can serve as influencers is also gaining traction. Autonomous AI agents can generate content and interact with users on social media with some of them also showcasing capabilities for managing their individual tokenized communities.<\/p>\n
The development and growth of these types of agents will set new precedents for identity of creators and community building approaches. Agentic AI has the potential to create completely new avenues for intellectual property management and decentralized entertainment.\u00a0<\/span><\/p>\n
3. Decentralized Governance with AI<\/b><\/h4>\n
Artificial intelligence agents also stand out as prominent candidates for transforming decentralized governance with diverse benefits. Decentralized Autonomous Organizations<\/a>, or DAOs experience issues like non-participation of voters and slow decision-making processes. Agentic AI offers the most promising solutions for optimizing the structure of DAOs and changing how they operate.\u00a0<\/span><\/p>\n
AI agents can read through complex governance proposals and evaluate their impact on the DAO treasury. Subsequently, agents can vote on behalf of token holders or design optimized counter-proposals. AI agents in advanced setups can serve as autonomous treasury managers that deploy capital according to the mandates approved by the community.<\/span><\/p>\n
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Challenges Expected in the Use of AI Agents in Web3<\/b><\/h3>\n
The benefits expected from AI agents in the domain of web3 clearly showcase that autonomous web3 systems driven by agentic AI have huge potential. However, it is important to address many critical hurdles to ensure widespread adoption of agentic AI in web3.<\/span><\/p>\n
1. Smart Contract Vulnerabilities<\/b><\/h4>\n
Do you know the link that connects AI agents with the world of web3? Smart contracts<\/a> play a major role in bridging the gap between agentic AI systems and web3. Let us assume that the code of an agent or the smart contract that it interacts with has some vulnerability. It clearly implies that smart contract vulnerabilities<\/a> can lead to huge losses, especially due to instant draining of assets. Without appropriate guardrails, AI agents can execute thousands of faulty transactions before they notice anything wrong.<\/span><\/p>\n
2. Costs of On-chain Inference<\/b><\/h4>\n
The thought of using AI agents in web3 definitely sounds appealing with the assurance of numerous benefits. It is also important to know that running complex LLMs directly on blockchains is practically impossible due to high gas fees and scalability issues. AI agents have to do most of their cognitive processing outside the chain, primarily through decentralized compute networks and push the results to the blockchain<\/a>. Therefore, bridging the gap between AI agents and web3 without introducing centralization or latency is still a huge challenge.<\/p>\n
Final Thoughts\u00a0<\/b><\/h3>\n
The combination of AI agents and the web3 space stand for a fundamental evolution in how we perceive both technologies. Blockchain networks can empower AI agents with identity and economic tools to function as self-sovereign entities. On the other hand, AI agents can help in creating autonomous blockchain systems with a cognitive layer that performs complex interactions without human intervention. The future of autonomous web3<\/a> and blockchain systems is already here with AI agents, and you need to prepare for it now.<\/p>\n
The post AI Agents in Web3: The Future of Autonomous Blockchain Systems<\/a> appeared first on 101 Blockchains<\/a>.<\/p>\n
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- The use of agentic AI in web3 will empower agents to interact with decentralized applications<\/a> and smart contracts without depending on centralized intermediaries.<\/span><\/li>\n
- A survey by LangChain in 2024 found that around 51% of professionals used AI agents in production with 78% actively planning to implement them soon. (<\/span>Source<\/span><\/a>)<\/span><\/li>\n<\/ul>\n