As early as the end of 2023, 'AI+' was one of the keywords in the mainstream track predictions of major investment research institutions for Web3. Now, a year later, what has happened to 'AI+'?
Recently, a16z and VanEck released their 2025 Web3 predictions, all pointing to the same topic: AI agents and the latest development direction of AI+. Among them, AI agent investment stands out, achieving impressive results in the second half of 2024—within a day of its launch, the market value of Ai16z and its backing DAOS.FUN soared to $80 million, creating a new investment boom in AI crypto funds.
This has also piqued lawyer Mankun's curiosity, as he has long advised crypto investors to participate through crypto funds. Can the emergence of AI crypto funds provide smarter investment paths for crypto investors?
In this article, lawyer Mankun explores the new investment trend of AI crypto funds.
What is an AI crypto fund?
AI crypto funds, as the name suggests, fundamentally rely on artificial intelligence (AI) to replace traditional human management in investment decision-making processes, enabling fully automated operations on-chain, from data analysis to decision execution, without human intervention. Unlike traditional crypto funds that depend on the experience and intuition of fund managers, AI crypto funds utilize algorithmic models and on-chain data to achieve efficient and precise investment strategies through real-time calculations and executions.
The realization of AI crypto funds is thanks to the high transparency and democracy of Web3:
First, blockchain, as an infrastructure, provides AI machine learning models with rich and real-time data, extracting patterns from on-chain transaction history, asset price fluctuations, and market sentiment, which can help AI optimize investment strategies.
Secondly, the decentralized autonomous organization (DAO) framework provides an environment for AI crypto funds to operate without permission. The operations of AI crypto funds can be realized through smart contracts to achieve democratic governance and execution, further reducing subjectivity, operational risks, and centralization problems caused by human intervention.
It is precisely because of the nature of the underlying infrastructure that AI crypto funds' advantages are more pronounced compared to traditional crypto funds:
· Data processing capabilities. AI can analyze massive amounts of on-chain and off-chain data at high speed, accurately identify trends, and make decisions. This processing speed and data scale far exceed human limits.
· Market sentiment capture. By analyzing social media, news, and industry dynamics, AI can detect signals of market changes in advance, helping the fund make more accurate choices before trends occur.
· Autonomy and transparency. Relying on DAO and smart contracts, all operational records are on-chain, allowing AI to promote transparency in fund investment and management, increasing trust.
· Risk management capabilities. AI can conduct real-time monitoring and quickly adjust asset allocation based on market changes, giving AI crypto funds an advantage in facing market volatility.
As more capital engages with Web3, the demand from investors for efficient, robust, and transparent solutions has driven the emergence of AI crypto funds. The concept is indeed appealing, but implementation is key. So, what are the representative projects in this field?
What AI crypto funds are available?
Currently, the exploration in the field of AI crypto funds has achieved remarkable results. In addition to DAOS.FUN mentioned at the beginning by lawyer Mankun, there are also several AI crypto funds that have begun to experiment/run.
1.Ai16z and DAOS.FUN
As a phenomenon-level AI crypto fund, Ai16z attracted the attention of the entire industry as soon as it launched in the second half of 2024, successfully creating a boom in AI crypto investment. The decentralized autonomous organization (DAO) behind Ai16z—DAOS.FUN—is the core technical supporter of the fund, achieving governance transparency and decision automation through smart contracts. Ai16z relies on advanced AI algorithms and on-chain data analysis capabilities to truly realize full-process automation from strategy formulation to execution.
2.Yahctzee Fund
Yahctzee Fund, supported by crypto figure Arthur Hayes, is another noteworthy autonomous AI-driven fund. It demonstrates excellent flexibility and adaptability in investment decisions through on-chain governance structures and high-performance AI algorithms. The goal of Yahctzee Fund is not only to optimize returns but also to explore optimized paths for long-term asset allocation, attempting to create a more sustainable investment model.
3.Sekoia Virtuals
Sekoia Virtuals is an experimental AI fund initiated by Anand Iyer, managing partner of Canonical Ventures, focused on supporting the Virtuals ecosystem. Although the market impact of this project is currently not significant, its focus on small community investment management in Web3 not only highlights its differentiated advantages but also broadens the vertical fields and directions for the development of AI crypto funds.
4.Cod3x and BigTonyXBT
Cod3x is an organization focused on building next-generation AI agent infrastructure, and its flagship project BigTonyXBT is an autonomous trader based on the Base chain. BigTonyXBT focuses on the DeFi sector, gradually building a complete ecosystem for AI crypto funds in financial investment through AI automated trading and asset management functions.
All of the above projects focus on different aspects from technical implementation to ecological layout, comprehensively promoting the model innovation of crypto funds. However, while AI crypto funds showcase their huge potential, whether they can achieve compliance in the increasingly clear global regulatory environment is also a key issue—compliance determines whether they can truly inject sustainable growth momentum into the Web3 ecosystem.
Exploration of AI crypto fund compliance
The emergence of AI crypto funds undoubtedly brings innovation to the crypto investment field, but whether this emerging model is compliant remains an unresolved issue. This mainly stems from the uniqueness of AI crypto funds:
First, there is the issue of legal entities. Traditional funds must go through the approval of judicial jurisdictions when established and have a clear legal identity. However, most AI crypto funds seen so far often operate based on DAOs, which have not been explicitly recognized as legal entities in most countries. This means that if an AI crypto fund involves asset custody, contract signing, or legal disputes, the existing legal framework may not provide effective support. In some jurisdictions, operating a fund without a license may be viewed as illegal fundraising, which exposes AI crypto funds to greater legal risks in cross-border operations.
Next is the issue of licensing and regulation. Existing financial market rules require fund managers to obtain relevant licenses and fulfill regulatory obligations, such as disclosing risks to investors, regularly reporting fund performance, etc. However, AI crypto funds do not have a clear manager; investment strategies and execution are completed by AI algorithms, making it a compliance challenge to define the identity of the 'fund manager'. Additionally, this 'unlicensed operation' model may be viewed as regulatory avoidance, especially in regions like the United States and Europe, where strict regulations exist for fund establishment and management, posing a significant barrier to the compliance of AI crypto funds.
Third, there are issues of governance transparency and algorithm compliance. Although the DAO structure provides technical support for on-chain transparent governance of AI crypto funds, this transparency is more directed at technology and the community, rather than regulatory agencies. Traditional funds are required to disclose their investment strategies and governance structures to regulatory bodies, but the algorithms of AI crypto funds are complex and not easily explained. Whether regulatory agencies can accept such 'black box' operations remains questionable. Especially in regions like Europe, where there are explicit requirements for algorithm transparency and interpretability, AI crypto funds may face greater compliance pressures.
Furthermore, AI crypto funds typically serve the global market, but various countries have inconsistent regulatory attitudes towards crypto assets and AI technologies. For example, the U.S. Securities and Exchange Commission may view them as unregistered securities, while in China, all activities involving cryptocurrencies are explicitly prohibited, potentially preventing AI crypto funds from conducting business due to policy violations. This inconsistency in regional regulations poses additional compliance challenges for AI crypto funds when expanding operations.
Moreover, whenever AI is mentioned, data privacy and cross-border issues are always unavoidable core regulatory topics. Currently, many countries and regions around the world have begun to establish AI-related regulatory legislation, such as China's Ministry of Industry and Information Technology deciding to set up a standardization technical committee for artificial intelligence responsible for revising industry standards; Europe's EU AI Act is gradually advancing, aiming to classify the risk levels of AI applications and establish strict transparency and data usage requirements; the Blueprint for an AI Bill of Rights released by the White House, although merely a principled guideline, explicitly states the basic principles of algorithm transparency, user privacy protection, and the prevention of data abuse. The gradual establishment of these regulatory rules will also impose stricter requirements for the compliance of AI crypto funds.
Lawyer Mankun summarizes
The emergence of AI crypto funds has brought a new imaginative space to the field of crypto investments. Lawyer Mankun believes that AI crypto funds are not only a technological innovation but also a challenge to traditional financial logic. However, whether it be the legal status of DAOs, the interpretability of AI algorithms, or the diversity of the global regulatory environment, compliance remains the key factor determining whether AI crypto funds can enter the mainstream.
Although there remain significant gaps between traditional regulatory frameworks and new technologies, developers and investors should also strive to: actively adapt to existing legal frameworks, while preparing for future regulatory rules amidst uncertainty.
Lawyer Mankun believes that only by seeking innovation within compliance and creating value within rules can AI crypto funds inject sustainable development momentum into the entire industry.