Grayscale: How AI Agents + Blockchain Change the Crypto World?

Source: Grayscale; Compiled by: Baishui, Golden Finance

Abstract

• In the future, AI agents will revolutionize 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 will need more than just intelligence — they will need economic autonomy. Fortunately, blockchain is well suited for this purpose — as recent experiments with AI “influencers” have demonstrated.

• AI influencers — autonomous chatbots that run on social media — can operate their own blockchain wallets. What’s more, they can understand economic incentives and leverage resources to help achieve their goals.

• Grayscale Research believes that the increase in AI’s use of blockchain in payments and other financial services could benefit multiple crypto market sectors. 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 AI robots use their massive computing power to promote memecoins and accidentally become digital millionaires. That future is here.

An “AI agent” is a piece of software that can act independently in pursuit of a complex set of goals. For example, you could ask an AI agent to organize a multi-city vacation and arrange flights, book accommodation, and schedule activities based on your preferences and budget. But to accomplish these tasks, the AI ​​agent needs control over economic resources and the ability to send and receive payments.

That's where blockchain comes into play. In the traditional financial world, AI agents face restrictions 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 example, an AI agent called Truth Terminal has made a splash for being the "first AI agent millionaire." [1] Operating autonomously on X (formerly Twitter), Truth Terminal behaves like a normal human influencer: tweeting and engaging with other users, seemingly months after its launch, Truth Terminal expressed interest in the new memecoin ($GOAT) after receiving a deposit of it. Through an associated blockchain address, Truth Terminal subsequently promoted the token to its followers, sparking interest and causing its value to rise by about 9x (Exhibit 1).

While inherently amusing, Truth Terminal and related AI influencer projects are demonstrating that blockchain technology can be an effective tool for mediating economic value between humans, AI agents, and cyber-physical devices, with potential implications for multiple areas of the cryptocurrency market.

Exhibit 1: GOAT has performed particularly well since being endorsed by Truth Terminal

Understanding AI Agents

AI agents are advanced artificial intelligence systems designed to operate autonomously in complex environments[2]. These digital entities have the ability to perceive, reason, and take independent actions to achieve their goals. Some of the key characteristics of AI agents include autonomy, responsiveness, proactive behavior, social interaction, and the ability to continuously learn. By combining these characteristics, AI agents can adapt to new situations, make decisions, learn, and change behavior over time.

Initially, AI research focused on developing expert systems and knowledge bases for specific problem-solving tasks. However, the 1990s saw a paradigm shift towards creating more general, autonomous agents capable of operating in dynamic environments. Concurrent advances in machine learning, particularly reinforcement learning, further enhanced the ability of these agents 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 such as Apple’s Siri (launched in 2010) and Amazon’s Alexa (launched in 2014) exemplify how AI agents can use natural language processing to interact with users. In 2016, DeepMind’s AlphaGo defeated the world champion of Go, a landmark achievement in gaming AI. In the financial sector, AI-powered trading bots have revolutionized market operations, using complex algorithms to make split-second decisions in volatile trading environments.

The Case for AI Agents

To gain greater autonomy and achieve their goals, AI agents require financial services to accumulate and allocate resources. The permissionless nature of blockchain technology, coupled 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 a blockchain, but innovation has quickly expanded to include a range of experimental projects related to AI influencers.

A prime example of an AI influencer using blockchain technology is Luna, which was developed on Virtual Protocol. To the user, Luna appears as a female anime image and an associated chatbot (Exhibit 2). Essentially, Luna is on a mission to reach 100,000 followers on X. [3] This goal, and all of Luna’s actions, will ultimately make her operations transparent.

Luna functions similarly to a chatbot and interacts with X users (e.g., starting conversations and replying to tweets) to achieve her goals. However, Luna’s capabilities extend far beyond just tweeting. For example, if a user interacts with her tweets, she can financially compensate (“tip”) the user by sending Luna tokens to the user’s crypto wallet[4], thereby providing a direct link between Luna’s goal (reaching 100,000 users) and her economic resources. In short, Luna is a wealthy AI agent.

Exhibit 2: Screenshot of Luna, the AI ​​influencer 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 this mean for cryptocurrency investors? We see impacts in three main areas:

• Stablecoin issuers:Stablecoins are likely to be the primary choice for AI agent transactions. In this scenario, potential beneficiaries include stablecoin issuers and companies that integrate stablecoins and AI agents.This includes centralized stablecoin providers such as Tether, Circle, and leading payments company Stripe[5] (which recently acquired stablecoin company Bridge[6] for $1 billion), as well as decentralized stablecoin providers such as Maker/Sky. Another company to watch is Skyfire, a startup developing AI agents for stablecoin payments that recently raised funding from Coinbase Ventures and a16z crypto. [7]

• Low-cost/high-throughput chains:If AI agents end up using blockchain primarily as their underlying payment infrastructure, certain smart contract platforms may also benefit greatly from an influx of users and increased activity and fee revenue.Smart contract platforms that may benefit include high-throughput blockchains such as Solana; Ethereum Layer 2 BASE, which has launched an Ai agent framework tool that benefits from the security of Ethereum's underlying network; and Near, which positions itself as a blockchain for AI. [8]In addition, other smart contract platforms that may benefit include those that specialize in stablecoin payments, including Tron and Celo.

• DeFi:Decentralized financial applications may benefit; since they already exist on the blockchain, AI agents can easily use them. One could imagine AI agents autonomously staking tokens for rewards, participating in governance proposals for DAOs, or even providing liquidity on decentralized exchanges (DEXs). Applications we believe would particularly benefit 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 could also benefit. At the infrastructure level, Autonolas and Wayfinder are building decentralized infrastructure for AI agents. Protocols like Virtuals, Aether, and MyShell are building consumer AI agent applications. This category is nascent but has grown its share of the AI-themed pie over the past month.

Chart 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 signals a potential shift in the way AI agents interact with currency. Grayscale Research believes that the future of the internet may be increasingly 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 scenario becomes a reality, AI agents could become the primary way to get a large number of users into cryptocurrencies without them even knowing they are using blockchain technology. As such, AI agents have the potential to significantly impact cryptocurrency adoption and development, making this emerging topic an important area to monitor in the future.

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 conduct financial transactions autonomously. This is achieved through the Coinbase MPC (Multi-Party Computation) wallet, with both Coinbase and the development team holding key shards, allowing Luna to seamlessly call the API to make transactions. Luna owns 5% of her eponymous token, which is controlled by the team and distributed to her over time.

[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