Article source: Mankun Blockchain
As early as the end of 2023, 'AI+' was one of the keywords in the mainstream track predictions of major research institutions in Web3. Now, a year later, how is 'AI+' doing?
Recently, a16z and VanEck released their 2025 Web3 predictions, all pointing to the same topic: AI agents, the latest development direction of AI+. Among them, AI agent investment stands out, achieving remarkable results in the second half of 2024—after just one day of release, the market value of Ai16z surged to 80 million U.S. dollars, sparking a new wave of AI investment with 'AI crypto funds.'
This also piqued lawyer Mankun's curiosity. After all, for a long time, lawyer Mankun has recommended that crypto investors participate through crypto funds. Can the emergence of AI crypto funds provide crypto investors with a more intelligent investment path?
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, have a core logic of using artificial intelligence (AI) to replace traditional human management in investment decision-making, achieving full-process automation on-chain, from data analysis to decision execution, without human intervention. Unlike traditional crypto funds that rely on the experience and intuition of fund managers, AI crypto funds rely on algorithm models and on-chain data to achieve efficient and precise investment strategies through real-time calculation and execution.
The realization of AI crypto funds is attributed to the high transparency and democracy of Web3:
Firstly, blockchain, as infrastructure, provides AI machine learning models with rich and real-time data, extracting patterns from on-chain trading history, asset price fluctuations, to market sentiment. This data can help AI optimize investment strategies.
Secondly, the decentralized autonomous organization (DAO) structure provides a permissionless operating environment for AI crypto funds. The operation of AI crypto funds can achieve democratic governance and execution through smart contracts, further reducing the subjectivity, operational risks, and centralization issues brought by human intervention.
It is precisely because of the characteristics of the underlying infrastructure that, compared to traditional crypto funds, the advantages of AI crypto funds are more pronounced:
· Data processing capability. AI can analyze vast amounts of on-chain and off-chain data at high speed, accurately identifying trends and making 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 funds make more accurate choices before trends occur.
· Autonomy and transparency. Relying on DAOs and smart contracts, all operational records are on-chain, allowing AI to promote transparency in fund investment and management, increasing trust.
· Risk management capability. AI can not only monitor in real-time but also quickly adjust asset allocations based on market changes, giving AI crypto funds an advantage in the face of market volatility.
As more capital participates in Web3, the demand from investors for efficient, robust, and transparent solutions has driven the birth of AI crypto funds. The concept is certainly good, but implementation is key. So, what are the representative projects in this field?
What AI crypto funds are available?
Currently, explorations in the field of AI crypto funds have already achieved notable success. In addition to DAOS.FUN mentioned by lawyer Mankun at the beginning, there are several AI crypto funds that have begun to experiment/run.
1. Ai16z and DAOS.FUN
As a phenomenal AI crypto fund, Ai16z attracted the attention of the entire industry when launched in the second half of 2024, successfully riding the wave of 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-making 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
Supported by crypto figure Arthur Hayes, Yahctzee Fund is another notable 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, aiming 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, focusing on supporting the Virtuals ecosystem. Although the current market impact of this project is not substantial, its focus on investment management in small Web3 communities not only highlights its differentiated advantages but also broadens the development of AI crypto funds into more vertical fields and directions.
4. Cod3x and BigTonyXBT
Cod3x is an organization focused on building the next generation AI agent infrastructure, and its flagship project BigTonyXBT is an autonomous trader based on the Base chain. BigTonyXBT focuses on the DeFi field, gradually building a complete ecosystem for AI crypto funds in financial investment through AI automated trading and asset management functionalities.
All these projects, from technical implementation to ecological layout, have their own focus and comprehensively promote the innovative models of crypto funds. However, while AI crypto funds showcase their immense potential, whether they can achieve compliance in a gradually clarifying 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 has undoubtedly brought innovation to the crypto investment field, but whether this emerging model is compliant remains an unresolved question. This mainly comes down to the uniqueness of AI crypto funds:
Firstly, there is the issue of legal entities. Traditional funds must undergo approval from the judicial jurisdiction during establishment and possess a clear legal identity. However, most AI crypto funds observed so far often operate based on DAOs, which have not been explicitly recognized as legal entities in most countries. This means that if AI crypto funds are involved in 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 considered illegal fundraising, leading to greater legal risks for AI crypto funds in cross-border operations.
Secondly, there are issues regarding licenses and regulation. Existing financial market rules require fund managers to obtain relevant licenses and fulfill regulatory obligations, such as disclosing risks to investors and regularly reporting fund performance. However, AI crypto funds do not have a clearly defined 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 seen as evading regulation, particularly in regions like the U.S. and Europe, where there are strict regulations regarding fund establishment and management, posing a significant obstacle to the compliance of AI crypto funds.
The third issue is 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 towards technology and community rather than regulatory agencies. Traditional funds need to disclose their investment strategies and governance structures to regulatory bodies, but the algorithms of AI crypto funds are complex and not easily interpretable, raising questions about whether regulators can accept such a 'black box' operational model. Especially in regions like Europe, where there are explicit requirements for algorithm transparency and interpretability, AI crypto funds may face greater compliance pressures.
Additionally, AI crypto funds typically serve global markets, but the regulatory attitudes towards crypto assets and AI technology vary from country to country. For example, the U.S. Securities and Exchange Commission may view them as unregistered securities, while in China, all activities related to cryptocurrencies are explicitly prohibited, which may prevent AI crypto funds from operating due to violating policy bottom lines. This inconsistency in regional regulation poses more compliance challenges for AI crypto funds as they expand their business.
Moreover, whenever AI is mentioned, data privacy and cross-border issues are always unavoidable regulatory core 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 technical committee for AI standardization to revise industry standards; the European Union's AI Act is gradually advancing, aiming to classify AI applications by risk level and establish strict requirements for transparency and data usage; the U.S. White House's Blueprint for an AI Bill of Rights, although a principle-based guide, also clearly puts forward basic principles for algorithm transparency, user privacy protection, and data misuse prevention. The gradual establishment of these regulatory rules will also impose stricter requirements for the compliance of AI crypto funds.
Summary by lawyer Mankun
The emergence of AI crypto funds has brought a new realm of imagination to the crypto investment field. Lawyer Mankun believes that AI crypto funds are not only a technological innovation but also a challenge to traditional financial logic. However, whether it is the legal status of DAOs, the interpretability of AI algorithms, or the diversity of the global regulatory environment, compliance is always the key factor determining whether AI crypto funds can go mainstream.
Although there remains a significant gap between existing regulatory frameworks and new technologies, developers and investors should strive to both actively adapt to the current legal framework and prepare for future regulatory rules amid uncertainty.
Lawyer Mankun believes that only by seeking innovation within compliance and creating value within the rules can AI crypto funds inject sustainable development momentum into the entire industry.