2025 Web3 Investment Trend: The Potential and Regulatory Challenges of AI Crypto Funds
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2025 Web3 Investment Trend: The Potential and Regulatory Challenges of AI Crypto Funds
AI cryptocurrency funds are not merely a technological innovation, but also a challenge to traditional financial logic.
Navigating Web3 tides with focused insightsBy: ManQin Blockchain Legal Services
As early as the end of 2023, "AI+" was already one of the key themes forecasted by major research institutions for mainstream Web3 sectors. Now, a year later, how has AI evolved?
Recently, a16z and VanEck released their 2025 Web3 predictions, both highlighting the same trend: AI agents—the latest evolution in the "AI+" space. In particular, AI agent investing stood out in the second half of 2024—Ai16z, which reached an $80 million market cap within a day of launch, along with its underlying platform DAOS.FUN, sparked a new wave in crypto investment known as the “AI Crypto Fund.”
This development piqued the interest of ManQin lawyers, who have long advised crypto investors to participate through crypto funds. With the emergence of AI crypto funds, could this offer investors a smarter investment path?
In this article, ManQin lawyers explore this emerging investment trend—AI crypto funds.
What Is an AI Crypto Fund?
An AI crypto fund, as the name suggests, replaces traditional human management with artificial intelligence (AI) to make investment decisions, enabling fully automated on-chain operations—from data analysis to execution—without human intervention. Unlike traditional crypto funds that rely on fund managers’ experience and intuition, AI crypto funds leverage algorithmic models and on-chain data to execute efficient, precise investment strategies through real-time computation and execution.
The feasibility of AI crypto funds stems from Web3’s high transparency and decentralization:
First, blockchain infrastructure provides AI machine learning models with rich, real-time data. By identifying patterns in on-chain transaction history, asset price fluctuations, and market sentiment, these datasets help AI refine investment strategies.
Second, decentralized autonomous organization (DAO) architecture offers a permissionless operating environment for AI crypto funds. Through smart contracts, governance and execution can be democratized, further reducing subjectivity, operational risks, and centralization issues associated with human involvement.
Thanks to these foundational characteristics, AI crypto funds offer distinct advantages over traditional crypto funds:
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Data Processing Capability: AI can rapidly analyze vast volumes of on- and off-chain data, accurately identify trends, and make decisions—speed and scale far beyond human capability.
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Market Sentiment Capture: By analyzing social media, news, and industry developments, AI can detect early signals of market shifts, enabling the fund to act before trends fully emerge.
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Autonomy and Transparency: Powered by DAOs and smart contracts, all operations are recorded on-chain, enhancing transparency in fund management and building trust.
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Risk Management: AI enables real-time monitoring and rapid portfolio rebalancing in response to market changes, giving AI crypto funds a stronger edge during volatility.
With increasing capital entering Web3, investor demand for efficiency, stability, and transparency has driven the emergence of AI crypto funds. While the concept is promising, execution is key. So, what are some representative projects in this space?
Notable AI Crypto Funds
The exploration of AI crypto funds has already yielded significant results. Beyond DAOS.FUN mentioned earlier, several other projects are actively testing or operating AI-driven funds.
1. Ai16z and DAOS.FUN
Ai16z emerged in the second half of 2024 as a breakout AI crypto fund, capturing widespread industry attention and igniting the AI crypto investment trend. The decentralized autonomous organization (DAO) behind Ai16z—DAOS.FUN—serves as the core technical enabler, achieving transparent governance and automated decision-making via smart contracts. Leveraging advanced AI algorithms and on-chain data analytics, Ai16z realizes full automation from strategy formulation to execution.
2. Yahctzee Fund
Backed by well-known crypto figure Arthur Hayes, the Yahctzee Fund is another notable autonomous, AI-driven fund. Utilizing on-chain governance and high-performance AI algorithms, it demonstrates exceptional flexibility and adaptability in investment decisions. Beyond optimizing returns, Yahctzee Fund aims to explore sustainable long-term asset allocation strategies, striving to build a more resilient investment model.
3. Sekoia Virtuals
Sekoia Virtuals is an experimental AI fund initiated by Anand Iyer, managing partner at Canonical Ventures, focusing on supporting the Virtuals ecosystem. Though currently limited in market impact, its focus on small Web3 community investment management offers clear differentiation and opens up new verticals and directions for AI crypto fund development.
4. Cod3x and BigTonyXBT
Cod3x is an organization dedicated to building next-generation AI agent infrastructure. Its flagship project, BigTonyXBT, is an autonomous trader built on Base chain. Focused on DeFi, BigTonyXBT leverages AI-powered automated trading and asset management to gradually establish a complete financial ecosystem for AI crypto funds.
These projects differ in technical implementation and ecosystem focus but collectively drive innovation in the crypto fund model. However, while showcasing immense potential, the ability of AI crypto funds to achieve compliance amid increasingly defined global regulations remains a critical challenge—compliance will determine whether they can truly deliver sustainable growth to the Web3 ecosystem.
Compliance Challenges for AI Crypto Funds
The emergence of AI crypto funds brings innovation to crypto investing, but their regulatory compliance remains unresolved. This stems primarily from the unique nature of AI crypto funds:
First, legal entity status. Traditional funds must be established under a recognized jurisdiction and possess a clear legal identity. However, most current AI crypto funds operate via DAOs, which are not legally recognized entities in most countries. This means existing legal frameworks may fail to support them in cases involving asset custody, contract signing, or disputes. In some jurisdictions, unlicensed fund operations could be deemed illegal fundraising, posing greater legal risks for cross-border activities.
Second, licensing and regulatory obligations. Existing financial regulations require fund managers to obtain licenses and fulfill reporting duties—such as disclosing risks and publishing performance reports. But AI crypto funds lack a clearly defined manager; investment strategies and execution are entirely algorithm-driven. Defining the “fund manager” under current laws presents a fundamental compliance hurdle. Moreover, operating without a license may be seen as regulatory evasion—particularly problematic in strictly regulated regions like the U.S. and Europe.
Third, governance transparency and algorithmic compliance. While DAO architecture enables on-chain transparency for technical and community purposes, this does not necessarily meet regulatory standards. Traditional funds must disclose investment strategies and governance structures to regulators. Yet AI crypto fund algorithms are often complex and opaque. Regulators may question whether such “black box” systems are acceptable—especially in regions like Europe, where algorithmic explainability and transparency are legally mandated.
Additionally, AI crypto funds typically target global markets, but regulatory attitudes toward crypto assets and AI technologies vary widely. For example, the U.S. Securities and Exchange Commission might classify them as unregistered securities, while China explicitly bans all cryptocurrency-related activities, making it impossible for AI crypto funds to operate there. This regulatory fragmentation creates significant compliance barriers for international expansion.
Furthermore, data privacy and cross-border data flows remain core regulatory concerns in AI. Countries and regions are increasingly establishing AI-specific regulations: China’s Ministry of Industry and Information Technology has formed an AI Standardization Technical Committee to develop industry standards; the European Union’s AI Act is progressing to classify AI applications by risk level and impose strict transparency and data usage requirements; and the White House’s Blueprint for an AI Bill of Rights, though non-binding, sets principles for algorithmic transparency, user privacy protection, and prevention of data misuse. As these regulatory frameworks take shape, AI crypto funds will face increasingly stringent compliance demands.
ManQin Lawyer Conclusion
The rise of AI crypto funds opens exciting new possibilities for crypto investing. ManQin lawyers believe these funds represent not just technological innovation, but also a challenge to traditional financial paradigms. However, issues such as the legal status of DAOs, the interpretability of AI algorithms, and the diversity of global regulations mean that compliance remains the key determinant of whether AI crypto funds can go mainstream.
While gaps persist between current regulatory frameworks and emerging technologies, developers and investors should proactively align with existing laws while preparing for future regulatory developments amid uncertainty.
ManQin lawyers believe that only by pursuing innovation within compliance and creating value within rules can AI crypto funds contribute sustained growth to the broader industry.
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