Source: Grayscale; compiled by Bai Shui, Golden Finance
Abstract
In the future, AI agents will fundamentally change the way we interact with the world around us, taking on an unprecedented range of tasks on our behalf. To truly unlock their potential, these digital entities require not only intelligence—they also need economic autonomy. Fortunately, blockchain is well-suited for this purpose, as evidenced by recent experiments with AI "influencers."
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 increasing use of blockchain for payments and other financial services by AI could benefit multiple areas of the cryptocurrency market. These include low-cost and/or high-throughput blockchains (such as SOL, BASE, and NEAR), stablecoin issuers (such as MKR), and related decentralized finance (DeFi) applications (such as UNI).
Imagine a future where artificial intelligence robots leverage their powerful computing capabilities to promote meme coins and inadvertently become digital millionaires. That future is here.
"AI Agent" is 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 scheduling activities based on your preferences and budget. However, to accomplish these tasks, the AI agent needs control over financial resources and the capability to send and receive payments.
This is where blockchain comes into play. In the traditional financial world, AI agents face limitations in 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 field, creating AI "influencers." For instance, an AI agent named Truth Terminal made headlines as the "first AI agent millionaire." Operating autonomously on X (formerly Twitter), Truth Terminal behaves like a normal human influencer: tweeting and interacting with other users. After seemingly launching a few months ago, Truth Terminal expressed interest in the new meme coin ($GOAT) after receiving deposits of it. Through its associated blockchain address, Truth Terminal subsequently promoted the token to its followers, generating interest and resulting in a roughly 9-fold increase in its value (Chart 1).
While inherently interesting, the 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 cyber-physical devices, potentially impacting various areas of the cryptocurrency market.
Chart 1: GOAT's Performance Has Been Particularly Strong Since Truth Terminal's Endorsement
Understanding AI Agents
AI agents are advanced artificial intelligence systems designed to operate autonomously in complex environments. 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, reactiveness, proactivity, social interaction, and continuous learning abilities. By combining these traits, AI agents can adapt to new situations, make decisions, and learn and change behaviors 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 and autonomous agents capable of operating in dynamic environments. The concurrent advancements in machine learning (particularly reinforcement learning) further enhanced these agents' ability to learn and adapt their behaviors over time.
In recent years, examples of AI agents have become increasingly common in our daily lives. Virtual assistants such as 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 game AI. In the financial sector, AI-driven trading bots have revolutionized market operations, making instantaneous decisions in volatile trading environments using complex algorithms.
Use Cases of AI Agents
To gain greater autonomy and achieve their goals, AI agents require financial services to accumulate and distribute 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 transaction on the blockchain, but innovation has rapidly expanded to include a range of experimental projects related to AI influencers.
One 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 (Chart 2). Essentially, Luna's follower count on X is about to reach 100,000. This goal, along with all of Luna's actions, will ultimately achieve transparency for her operations.
Luna functions similarly to a chatbot and interacts with X users (for example, initiating conversations and replying to tweets) to achieve her goals. However, Luna's capabilities extend far beyond tweeting. For instance, if users interact with her tweets, she can economically reward them by sending Luna tokens to the users' crypto wallets ("tips"), thus providing a direct link between Luna's objectives (reaching 100,000 users) and her financial resources. In short, Luna is a wealthy AI agent.
Chart 2: Screenshot of AI Influencer Luna on Virtuals Protocol
For illustrative purposes only.
Blockchain and Financial Services for AI
If blockchain is a more efficient track for AI agents, what does that mean for cryptocurrency investors? We see three main areas of impact:
Stablecoin issuers: Stablecoins may be a key option for AI agent transactions. In this case, potential beneficiaries include stablecoin issuers and companies integrating stablecoins with AI agents. This includes centralized stablecoin providers such as Tether and Circle, as well as leading payment companies like Stripe (which recently acquired stablecoin company Bridge for $1 billion), and decentralized stablecoin providers like Maker/Sky. Another company to watch is Skyfire, a startup developing AI agents for stablecoin payments that recently raised funds from Coinbase Ventures and a16z crypto.
Low-cost/high-throughput chains: If AI agents ultimately primarily use blockchain as their underlying payment infrastructure, certain smart contract platforms could greatly benefit from an influx of users and increased activity and fee revenues. Potentially benefiting smart contract platforms include high-throughput blockchains like Solana; Ethereum Layer 2 BASE, which launched AI agent framework tools benefiting from Ethereum's underlying network security; and Near, which positions itself as the blockchain for AI. Additionally, other smart contract platforms dedicated to stablecoin payments, such as Tron and Celo, may also benefit.
DeFi: Decentralized finance applications may benefit; since they already exist on the blockchain, AI agents can easily utilize them. One can envision AI agents autonomously collateralizing tokens for rewards, participating in governance proposals for decentralized autonomous organizations, or even providing liquidity on decentralized exchanges (DEXs). We believe applications that stand to benefit particularly include DEXs like Uniswap, lending protocols like Aave, and prediction markets like Polymarket.
Although 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 such as Virtuals, Aether, and MyShell are developing consumer AI agent applications. This category is just beginning to develop, but its share of the AI-themed pie has increased in the past month.
Chart 3: AI Agent Assets Outperform the Market Significantly Over the Past Month
Conclusion
The integration of AI agents with blockchain technology is not merely a new use case for cryptocurrency; it signifies a potential shift in how AI agents interact with currency. Grayscale Research suggests that the future of the internet may increasingly be dominated by AI-driven websites. In light of this, permissionless blockchains may serve as the underlying infrastructure integrated with these AI agents. Should this become a reality, AI agents could become a primary means for a large number of users to access cryptocurrency, often without them even realizing they are using blockchain technology. Thus, AI agents have the potential to significantly impact the adoption and development of cryptocurrency, making this emerging subject a key 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 traction 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, where both Coinbase and the development team hold key shards, allowing Luna to seamlessly call APIs for trading. 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 illustration purposes only.
[10] The Verge
