The possibilities of applying artificial intelligence to automate the financial decision-making process from analysis of market situation to performing transactions based on the predefined rules are being explored.
For decentralized finance, the main question arising in this regard is what kind of infrastructure AI will require to be able to operate in blockchain markets.
Even though autonomous trading involves serious risks, several projects have been already working on developing necessary tools for it.
1. Orbs: Onchain Execution Infrastructure
Orbs is developing infrastructure for advanced decentralized trading, including protocols that support limit orders, time-weighted execution, and liquidity aggregation.
These capabilities are relevant to agent-driven trading because automated systems need reliable ways to translate trading decisions into executable transactions.
Orbs has also introduced Orbs Agentic, an initiative focused on connecting AI-driven systems with onchain trading capabilities. Its role within the emerging agent economy makes it an example of how existing DeFi infrastructure is adapting to new forms of automation. Orbs would be able to offer advanced execution through mechanisms that enable them to conduct trades more complex than just swaps on the market, making it possible for an AI entity to execute certain strategies with certain parameters, including price and execution time.
2. Fetch.ai: Autonomous Agent Infrastructure
Fetch.ai is developing infrastructure for autonomous software agents that can discover services, coordinate with other agents, and perform tasks on behalf of users. Its technology enables developers to build agents that communicate and collaborate to complete tasks with less direct human involvement, with potential applications in commerce, data exchange, and financial services.
In DeFi, this infrastructure could help AI agents identify opportunities across decentralized applications, compare available services, and coordinate multistep financial workflows based on user-defined goals or changing market conditions. While this coordination layer differs from dedicated onchain trading execution, it could complement blockchain infrastructure as autonomous agents take on more complex financial tasks.
3. Chainlink: Connecting Smart Contracts With External Systems
AI-driven financial applications may depend on information and services that exist outside the blockchain. Chainlink provides oracle and interoperability infrastructure that can help decentralized applications access external data and communicate across different blockchain environments.
Chainlink’s data feeds can be beneficial to AI agents in DeFi since they will be a source of information that will assist them to make decisions using the price and other external data. On the other hand, Chainlink’s platform is able to facilitate cross-chain operations, thus enabling coordination of the financial transactions of AI agents on different blockchains.
4. Safe: Managing Transaction Permissions
As automated systems gain the ability to initiate transactions, security and authorization become increasingly important.
Safe provides smart account infrastructure that can support configurable transaction permissions and account controls. This type of infrastructure may play an important role in ensuring automated financial systems operate within clearly defined boundaries.
The creation of AI agents within the DeFi space is unlikely to be contingent upon a singular protocol. Rather, it is likely to necessitate several layers of infrastructure relating to decision-making, market information, execution, interoperability, and security. Initiatives operating in each of these categories are starting to build the necessary foundations for the construction of such an ecosystem.