How DeFi AI Protocols Are Shaping the Future of Financial Services

Decentralized finance is one of the ecosystems best prepared for rapid evolution and adaptation. The sector is regularly expanded with new investment instruments and hopeful development teams promising to change the world of finance forever. One of the recent hot topics in the DeFi sector is the implementation of artificial intelligence.

A wide range of DeFi AI protocols focus on providing advanced financial services. Some projects offer AI agents as a product. For instance, the category of tracked AI agent protocols contains 10 startups with a total value locked close to $74 million.

There are several problems that must be addressed before we jump into the issue at hand:

• The difficulty of assessing the performance. Just like in the case of any other financial instrument, we need historical data and context to evaluate produced outcomes. Artificial intelligence is not a novel technology, but the hype surrounding it is pretty recent. We still lack the necessary data and instruments to analyze AI properly.
• AI in decentralized finance is underutilized. Despite the seeming readiness of blockchain technology to integrate artificial intelligence agents, only a handful of projects are focused on building solutions that can operate on the chain. Even the recently praised DEFAI is mostly directed at CEXes and DEXes, the main concern of the development team being the quality of its algorithmic trading outcomes.
• AI must prove itself as a viable direction for the tech world. Currently, only large language models are creating the buzz on social media. AI agents can be used in many areas, but the general public is informed only about chatbots like ChatGPT or Claude. Generative AI is not the only way forward. However, we are still waiting to see how technological innovations are driving the evolution of DeFi AI protocols.

Lastly, the ethical implications of DeFi AI implementation are still up for debate. Any financial advice produced by an AI system or trade made by an algorithm created or managed by artificial intelligence can lead to financial losses. Who will be blamed for the shortcomings of these untested virtual experts that are often trained on low-quality data using outdated machine learning techniques?

With these issues out of the way, we can talk about the future of financial services in the context of the rapid adoption of artificial intelligence across centralized and decentralized finance ecosystems. We will discuss the advantages and risks associated with this technology and its use in the world of investment. Additionally, we will talk about some use cases that are proving to be very efficient and useful to end users.

What can be improved?

AI is still a buzzword that does not have many already existing use cases in the DeFi ecosystem. The vast majority of tracked protocols in the AI category are gaming, media, or entertainment projects, with the inclusion of some interesting protocols like Venice (a private, non-censorship generative AI), Virtuals Protocol (a marketplace for AI agents), and World of Dypians (a gaming project).

The impact of macroeconomic factors on the adoption of DeFi AI technologies is still noticeable, with multiple companies offering unique financial services. The Sirio Finance project by Hedera is a DeFAI lending and borrowing layer on the Hedera network that prevents liquidations by making smart adjustments to positions.

The limited choice of viable options in the DeFi AI sector creates a question: Which aspects of financial services can be improved?

• Risk management in DeFi is a very difficult topic to discuss because all projects have elevated risk levels compared to financial instruments like fixed-income assets or real estate. Artificial intelligence can be used to analyze various investment opportunities to choose the best options for each case. For instance, you can talk to Maneki AI at Rivo to find the right investment strategy based on your preferences and risk tolerance.
• Decentralized data collection. The world of DeFi is hard to navigate due to the vast ocean of unstructured data that finds itself in assorted packs all over different chains. Building a marketplace for decentralized data that can be used to create high-quality training sets can be a great way to further expand the value produced by the ecosystem as a whole. It is also a great way to elevate the importance of community and developer involvement in the success of DeFi AI projects.
• Tokenization of AI products. Virtual protocol has over 700 different agents that can be invested in. Partial ownership is a big part of the offer on this protocol. The combined TVL of all agents is close to $30 million, with some tokens like G.A.M.E. reaching over $18.73 million market cap. Decentralization allows for fractional ownership and many other ways to collectively manage, develop, and use AI agents.
• Personalization of financial services. We are all well aware of investment risks in DeFi. A smartly implemented AI can mitigate these dangers by providing expert-level advice and solid investment suggestions. For instance, you can use the Rivo Maneki AI, positioned as the Guardian of decentralized wealth, to interact with DeFi protocols, receive actionable insights, and find strategies that suit your preferences, portfolio, and risk style.
• Automation and higher efficiency. The industry already offers a wide range of fully automated investment strategies that do not require much oversight. Nevertheless, these are still purely mechanical algorithms that do not adjust to dynamic market conditions. The implementation of intelligent agents can solve this issue. Some projects, such as KAITO and Terminal, are slowly implementing AI features to improve investment outcomes.

One of the key issues for the whole DeFi sector is onboarding. User experience in financial services is often smoothed out as much as possible to ensure that users do not feel uncomfortable or lost using them. In the world of DeFi, this is still a very low priority for many protocols, making it hard for newcomers to get on board quickly.

Again, AI agents, such as Rivo Maneki AI, are capable of improving this area. For instance, Maneki AI offers tips on how to use the interface effectively, can explain some DeFi concepts to users, and offers them the best set of strategies to include in their portfolios based on their individual feedback.

The main takeaway

Artificial intelligence has huge potential even in its current, underdeveloped form. Some projects in the DeFi sector use them for liquidity and price prediction, while others implement them to enhance user experience and usability. The range of applications for AI is incredibly wide. The AI agent market alone is expected to reach $47.1 billion by 2030, and a significant portion of this market will be controlled by decentralized projects.

We strongly recommend using on-chain data aggregators like Dappradar and DeFiLlama. If you want to learn how to keep track of emerging trends and projects in the DeFi AI space, use these tools frequently. You can also read our blog and original stories or keep up with various developments in the world of DeFi!

Rivo is a great destination for all crypto enthusiasts who are interested in exploring promising investment strategies. The Rivo Maneki AI is also a great example of artificial intelligence implemented seamlessly to deliver a better user experience. Go and check out these exciting products now!