Web3 infrastructure company Biconomy has announced the integration of artificial intelligence (AI) agents to facilitate on-chain transactions, aiming to simplify and automate the trading process for users.
Biconomy’s Delegated Authorization Network (DAN) serves as an authorization layer, enabling users to delegate trading activities to AI agents.
This system allows these agents to manage and execute transactions autonomously, based on predefined instructions set by the user.
Co-founder Aniket Jindal explains that DAN can handle tasks ranging from automating routine actions to complex decision-making based on user preferences and market conditions.
Users provide specific instructions through a decentralized application (DApp), outlining their trading strategies and asset allocations.
For example, a user might instruct, “invest $1,000 following this strategy,” and the AI agent will execute accordingly.
This setup offers a high level of control and customization, making it easier for users to manage their investments without constant manual input.
While both AI agents and trading bots automate trading, AI agents offer greater complexity and adaptability.
They not only execute trades but also optimize asset allocation and portfolio management, adapting to dynamic market conditions based on pre-set criteria or learned experiences.
This makes them more versatile and efficient compared to traditional trading bots.
Biconomy ensures the security and privacy of transactions through a sharding mechanism.
Each user receives a unique delegated authorization key, which is split into multiple fragments and distributed across a decentralized network of nodes.
This ensures that no single node has access to the complete key, enhancing security.
The DAN network leverages Ethereum’s EigenLayer for economic security.
Validators in the EigenLayer network must restake their Ethereum holdings, facing penalties if malicious activity is detected, further safeguarding the network.
The market for AI agents in finance is poised for significant growth. By 2030, it is expected to reach $70.53 billion, driven by a compound annual growth rate of 42.8% from 2023 to 2030.
Financial institutions are increasingly adopting AI agents for various applications, including automated trading, risk management, and fraud detection.
