Key Takeaways:
DeFAI projects leverage AI in DeFi to simplify user interfaces, assist in completing complex tasks with a single click, and analyze data.
DeFAI tokens like Griffain and Hey Anon have demonstrated sharp growth over a month: 733% and 1400%, respectively.
If successful, DeFAI could address liquidity issues and reshape how users interact with decentralized protocols.
DeFAI, or Decentralized Finance (DeFi) + Artificial Intelligence (AI), has sparked interest across the crypto market. Many consider it a key narrative. But will it live up to the hype?
AI agents are currently among the most talked-about topics. Projects like Virtuals Protocol (VIRTUAL), ai16z (AI16Z), and aixbt by Virtuals (AIXBT) have seen growth driven by this popularity.
According to Dune, AI has become the top-performing narrative of the year with an 11% gain, surpassing meme coins at 5%. In the crypto market, attention is now shifting to DeFAI, which offers more practical applications of AI in decentralized finance.
Source: Dune
DeFi + AI: Is It the New Hit of the Season?
DeFi is a key part of the crypto world, but its tools are difficult to use and require beginners to adapt to them. This is especially true for trading on decentralized exchanges (DEXs), which are much more complex than their traditional finance counterparts, centralized exchanges (CEXs).
Let’s imagine scenario number one. Company A launched a bot using an AI agent that analyzes meme coins on Solana (SOL), which typically debut on DEXs. The bot examines trading volume (sharp rises or falls), liquidity levels, whale activity, price history, Fully Diluted Valuation (FDV), and other data.
It then classifies these coins and provides approximate profit and loss expectations. The bot can also handle this task if a trader wants to monitor changes in this data daily over a week.
For example, you want to buy meme coins launched no more than 2–3 days ago with low market caps but high trading volumes. The AI agent processes this request and decides whether to buy the meme coin based on its analysis.
Additionally, it can send a direct request to fund your DeFi wallet for purchasing the selected meme coin on a specific chain. This eliminates the need to perform multiple steps manually, as a single request is sufficient to complete the process.
This significantly simplifies the daily routine for traders trying to catch new meme coins before their potential pump. Moreover, this market is highly volatile and sometimes requires several hours of daily monitoring.
Now let’s imagine scenario number two. You recently started trading in the crypto market and decided to earn passive income through staking but lack the necessary expertise. You found an AI agent that analyzes staking protocol data.
For example, it examines the Annual Percentage Yield (APY), potential risks, differences between staking on Ethereum or Solana, requirements, the number of frozen assets, and other factors. Based on your preferences, the agent makes a decision.
These are precisely the kinds of problems AI agents aim to solve in decentralized finance. As crypto researcher hitesh.eth noted, the DeFAI concept is based on Large Language Models (LLM) for Web3.
Simply put, they make user interaction with protocols easier.
In this model, the user doesn’t work directly with the protocol but through AI. The agent analyzes the data and decides to perform an action based on the specified parameters.
What Are the Prospects for DeFAI?
DeFAI is a relatively new narrative in crypto space. However, with the growing interest in AI agents, it is gaining traction by offering practical and valuable use cases.
For instance, the AI agents introduced by Virtuals Protocols lean more toward entertainment and content creation than tools for on-chain data analysis. This does not preclude the platform from being used to deploy bots to address other tasks.
As DeFAI is still in its early stages, the number of projects in this space remains limited. Messari researcher Sam Ruskin has identified several examples, including Griffain (GRIFFAIN), Neur (NEUR), Wayfinder, and Hey Anon (ANON).
Griffain is one of the most popular projects in the DeFAI sector, holding the largest market capitalization among its peers at $375.2 million.
The token has also drawn attention due to its rapid growth. According to CoinGecko, GRIFFAIN began trading at $0.06 in early December and reached an all-time high (ATH) of $0.50 on 6 Jan., marking a 733% increase.
Source: CoinGecko
Griffain allows users to launch their own AI agents or use pre-existing templates on its platform. One of these agents enables the creation of meme coins and conducting airdrops. However, access to the platform is currently by invitation only.
The second-largest DeFAI token by market capitalization is Hey Anon (market cap: $175.4 million). The project currently operates through a Telegram bot.
Hey Anon is following a trajectory similar to Griffain. According to CoinGecko, its token price rose from $0.90 to $14 in just 10 days, reflecting a growth of approximately 1400%.
Source: CoinGecko
DeFAI: Is It As Good As It Seems?
If DeFAI protocols establish a niche in decentralized finance, they could bring significant changes. First, DeFi would become more accessible for beginners. Second, an influx of new users could address liquidity challenges, a key issue for decentralized protocols. Third, Increased adoption of decentralized products, including staking, restacking, games, and NFTs, could further accelerate development within these sectors.
However, DeFAI also raises some concerns. One key issue is that AI agents operate without human intervention. While this can be advantageous, it also introduces risks. For example, how can a project ensure its bot won’t malfunction and make incorrect decisions? If an AI agent manages your wallet for meme coin purchases, it could misallocate funds or sell ones at a loss.
Security is another unresolved issue, as using an AI agent requires connecting your wallet and giving it permission to execute transactions.
Additionally, questions remain about how effectively AI agents can process data across multiple chains simultaneously and make decisions based on this analysis.
It will take time to see how DeFAI is adopted on a larger scale and what challenges it might face.
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