Source: Grayscale; Compiled by Bai Shui, Jincai Finance
Summary
In the future, AI agents will fundamentally change how we interact with the world around us, taking on an unprecedented range of tasks on our behalf. To truly unleash their potential, these digital entities need more than just intelligence—they also require economic autonomy. Fortunately, blockchain is well-suited for this purpose—as recent experiments involving AI "influencers" have demonstrated.
AI influencers—autonomous chatbots operating on social media—can manage their own blockchain wallets. More importantly, they can understand economic incentives and leverage resources to help achieve their goals.
Grayscale Research believes that the increased use of blockchain for AI in payments and other financial services could benefit multiple areas of the cryptocurrency market. This includes low-cost and/or high-throughput blockchains (like SOL, BASE, and NEAR), stablecoin issuers (like MKR), and related decentralized finance (DeFi) applications (like UNI).
Imagine a future where AI robots leverage their powerful computing capabilities to promote meme coins and inadvertently become digital millionaires. That future is here.
An "AI agent" is a software that can act independently to pursue a set of complex goals. For example, you can ask an AI agent to organize a multi-city vacation, arranging flights, booking accommodations, and planning activities based on your preferences and budget. However, to accomplish these tasks, the AI agent needs to control economic resources and have the ability to send and receive payments.
This is where blockchain comes into play. In the traditional financial world, AI agents face limitations when accessing bank accounts and processing payments. In contrast, blockchain allows AI agents to directly access their own wallets and make payments without permission.
Researchers have recently made thought-provoking breakthroughs in this area, creating AI "influencers." For example, an AI agent named Truth Terminal made headlines as the "first AI agent millionaire." [1] Operating autonomously on X (formerly Twitter), Truth Terminal behaved like a normal human influencer: tweeting and interacting with other users, and seemingly showing interest in a new meme coin ($GOAT) after receiving deposits of it. Through an associated blockchain address, Truth Terminal subsequently promoted the token to followers, generating interest and causing its value to rise by about 9 times (Figure 1).
While inherently fascinating, Truth Terminal and related AI influencer projects are proving that blockchain technology can serve as an effective tool for mediating economic value between humans, AI agents, and networked physical devices, with potential implications for multiple domains of the cryptocurrency market.
Figure 1: Since the recognition by Truth Terminal, GOAT has performed particularly well
Understanding AI Agents
AI agents are advanced AI systems designed to operate autonomously in complex environments [2]. These digital entities possess the ability to perceive, reason, and take independent actions to achieve their goals. Some key characteristics of AI agents include autonomy, reactivity, proactivity, social interaction, and continuous learning capabilities. By combining these features, AI agents can adapt to new situations, make decisions, and learn and change behavior over time.
Initially, AI research focused on developing expert systems and knowledge bases for specific problem-solving tasks. However, a paradigm shift occurred in the 1990s towards creating more general, autonomous agents capable of operating in dynamic environments. The synchronous advancements in machine learning (particularly reinforcement learning) further enhanced these agents' ability to learn and adapt their behavior over time.
In recent years, examples of AI agents have become increasingly common in our daily lives. Virtual assistants like Apple’s Siri (launched in 2010) and Amazon’s Alexa (launched in 2014) illustrate how AI agents interact with users using natural language processing. In 2016, DeepMind's AlphaGo defeated the world champion in Go, marking a milestone achievement in the field of game AI. In the financial sector, AI-driven trading bots have revolutionized market operations by making instantaneous decisions in volatile trading environments using complex algorithms.
Cases of AI Agents
To gain greater autonomy and achieve their goals, AI agents need financial services to accumulate and allocate resources. The permissionless nature of blockchain technology, combined with programmable smart contracts, provides an ideal environment for AI agents to operate independently. Earlier this year, researchers conducted the first agent-to-agent transactions on the blockchain, but innovation is rapidly expanding and now includes a range of experimental projects related to AI influencers.
A major example of an AI influencer using blockchain technology is Luna, which was developed on the Virtuals Protocol. For users, Luna appears as a female anime image and a related chatbot (Figure 2). Essentially, Luna's follower count on X is about to reach 100,000. [3] This goal, along with all of Luna's actions, will ultimately achieve transparency in her operations.
Luna's functionality is similar to that of a chatbot and interacts with X users (for instance, starting conversations and replying to tweets) to achieve her goals. However, Luna's capabilities go far beyond tweeting. For example, if a user interacts with her tweet, she can economically reward the user by sending Luna tokens to their crypto wallet ("tips") [4], providing a direct link between Luna's goal (reaching 100,000 users) and her economic resources. In short, Luna is a wealthy AI agent.
Figure 2: Screenshot of AI influencer Luna on the Virtuals Protocol
For illustrative purposes only.
Blockchain and Financial Services for AI
If blockchain is a more effective track for AI agents, what does this mean for cryptocurrency investors? We see impacts in three main areas:
Stablecoin Issuers: Stablecoins could be a primary choice for AI agent transactions. In this case, potential beneficiaries include stablecoin issuers as well as companies integrating stablecoins and AI agents. This includes centralized stablecoin providers like Tether and Circle, leading payment companies like Stripe [5] (which recently acquired the stablecoin company Bridge for $1 billion [6]), and decentralized stablecoin providers like Maker/Sky. Another company to watch is Skyfire, a startup developing AI agents for stablecoin payments, which recently raised funds from Coinbase Ventures and a16z crypto. [7]
Low-cost/High-throughput Chains: If AI agents ultimately use blockchains primarily as their underlying payment infrastructure, certain smart contract platforms may greatly benefit from an influx of users and increased activity and fee revenue. Potentially benefiting smart contract platforms include high-throughput blockchains like Solana; Ethereum Layer 2 BASE, which launched AI agent framework tools that benefit from Ethereum's underlying network security; and Near, which positions itself as a blockchain for AI. [8] Additionally, other potentially benefiting smart contract platforms include those specializing in stablecoin payments, such as Tron and Celo.
DeFi: Decentralized finance applications could benefit; since they already exist on the blockchain, AI agents can easily utilize them. One can imagine AI agents autonomously collateralizing tokens for rewards, participating in governance proposals for decentralized autonomous organizations, and even providing liquidity on decentralized exchanges (DEX). We believe that particularly benefiting applications include DEXs like Uniswap, lending protocols like Aave, and prediction markets like Polymarket. [9]
While still a niche market, certain protocols related to AI agents may also benefit. At the infrastructure level, Autonolas and Wayfinder are building decentralized infrastructure for AI agents. Protocols like Virtuals, Aether, and MyShell are constructing consumer AI agent applications. The development of this category is just beginning, but its share of the AI-themed cake has increased over the past month.
Figure 3: AI Agent assets have significantly outperformed the market in the past month
Conclusion
The integration of AI agents with blockchain technology is not just a new use case for cryptocurrency; it signifies a potential shift in how AI agents interact with currency. Grayscale Research believes that the future of the internet may increasingly be dominated by AI-driven websites. With this in mind, permissionless blockchains have the potential to serve as the underlying infrastructure for AI agents integrated with these websites. If this comes to fruition, AI agents could become a primary means for large numbers of users to enter the cryptocurrency space, often without even realizing they are using blockchain technology. Thus, AI agents could greatly influence the adoption and development of cryptocurrencies, making this emerging topic an important area for future monitoring.
References
[1] CoinTelegraph
[2] The roots of AI agent research can be traced back to the 1950s, although the term "agent" did not gain prominence in the AI community until the 1980s.
[3] Luna is powered by the Llama AI model—one of Luna's most interesting features is her ability to autonomously conduct financial transactions. This is achieved through the Coinbase MPC (Multi-Party Computation) wallet, with both Coinbase and the development team holding key shards that allow Luna to seamlessly call the API for transactions. Luna owns 5% of her namesake token, which is controlled by the team and gradually allocated to her.
[4] https://x.com/luna_virtuals/status/1859300930220675406
[5] For illustrative purposes only.
[6] CoinDesk
[7] The Block
[8] CoinTelegraph
[9] For illustrative purposes only.
[10] The Verge
