Author: Gu Yu, ChainCatcher
Earlier this month, veteran crypto venture capital firm Variant announced the completion of a new fundraise of $222 million, further expanding its fund theme from the previous "digital ownership" to "autonomy."
This may seem like just another ordinary fundraise, but the signal behind it is not ordinary.
Jesse Walden, a partner at Variant, stated that in the future, the label of "crypto investor" may gradually disappear, becoming akin to "internet investors." In other words, crypto is no longer an independent, closed investment vertical, but more like an underlying technological paradigm, embedded within main channels such as AI, finance, social media, robotics, data, content, and consumer products.
This is perhaps also the most pragmatic response from crypto VCs facing the impact of AI: not to compete with AI for narratives, but to attempt to become the underlying financial rails of the AI world.
1. Crypto VCs Begin Blurring Boundaries
In recent years, the fundraising logic of crypto VCs has been primarily built on one premise: blockchain will give rise to a new set of platforms, protocols, and applications independent of the Web2 world.
As narratives such as DeFi, NFTs, GameFi, Layer1, Layer2, modularization, restaking, DePin, and RWA emerged one after another, this logic was once highly convincing. Funds that entered new narratives early enough could potentially reap returns far exceeding traditional equity investments through secondary market liquidity of tokens.
However, this logic is now faltering. The core reason is the significant weakening of the wealth effect within the crypto market itself. Bitcoin has fallen sharply this year, with many market views citing fund outflows from crypto ETFs, macro liquidity pressures, and investors shifting towards AI and large tech IPOs as important reasons. Meanwhile, AI and hard tech companies like SpaceX, OpenAI, and Anthropic continue to capture the attention of LPs and the secondary market, significantly undermining the scarcity of crypto assets in "growth stories."
This means crypto funds are not just competing with other crypto funds, but with all assets representing future growth. AI, robotics, space, defense tech, and energy infrastructure are all competing for the same pool of LP risk budget.
Against this backdrop, "investing only in crypto" has gradually transformed from a professional label into a potential constraint.
If LPs believe AI is the most important technological variable of the next decade, it's difficult for a fund to prove its irreplaceability solely by saying "we understand tokenomics better." Especially considering that over the past cycles, many crypto projects have failed to demonstrate real revenue, user retention, and application scenarios, instead leaving behind structural issues like high FDV, low circulation, airdrop farming, and on-chain zombie applications.
This is why more and more crypto VCs are proactively blurring their boundaries.
YZi Labs has already expanded its investment scope to three major directions: Web3, AI, and biotechnology, and this year participated in a $52 million funding round for AI industrial robotics company RoboForce.
According to a February report by The Wall Street Journal, Paradigm is seeking to raise up to about $1.5 billion for its next fund, expanding its investment scope from crypto to "frontier tech" such as AI and robotics, while continuing to invest in the crypto sector. In May, AI manufacturing company SendCutSend completed a $110 million funding round with participation from Paradigm.
In May, Haun Ventures announced the completion of a $1 billion new fundraise, expanding its investment scope to the AI agent space. Its founder Katie Haun stated that AI will "increasingly represent us in economic activities," and services need to adapt for this future.
2. AI Agents Could Be Crypto's True Large-Scale Adoption Application
In the past, crypto projects often tried to get users to use products for the sake of "decentralization," but reality has proven that the vast majority of users do not change their behavior based on ideology.
Today, the crypto industry finds itself in an awkward position: it still possesses unique capabilities like globalization, open finance, composability, asset issuance, and censorship resistance, but these capabilities have long lacked truly high-frequency, essential, and large-scale application entry points.
What is more likely to happen in the future is that users will not know they are using crypto, but AI agents, robots, financial applications, games, or content platforms will invoke stablecoins, wallets, smart contracts, and on-chain identities in the background.
From Variant's perspective, autonomy is not just automation. Automation solves whether machines can complete tasks for humans, while autonomy focuses on whether users truly control their own assets, identity, data, and decision-making power. Variant stated in an article that building autonomous systems requires solving a series of issues such as incentive mechanisms, law, governance, security, verification, policy, and geopolitical interfaces in adversarial markets, with digital ownership being an important pillar of autonomy.
"The ideas that fueled the Web3 movement will find new momentum in the AI era. We did a lot of experiments, and crypto initially wanted to be seen as the product itself. But ultimately, we found that crypto is the rails that underpin many products, and its growth story is just beginning," Jesse Walden said.
This is perhaps the most important cognitive correction in the crypto industry in recent years.
Crypto does not have to be the front-end application users open every day; it can become the economic settlement layer between machines and machines, humans and machines, and applications and applications in the AI era.
If an AI agent is to perform tasks on behalf of users, it needs a wallet; if it needs to autonomously purchase APIs, call computing power, pay for data, and subscribe to services, it needs a low-cost, global, programmable payment network; if it needs to carry identity, reputation, and assets across multiple platforms, it needs an open account system; if it needs the external world to trust the results of its actions, it needs verification and audit mechanisms.
These issues are precisely within the scope of capabilities crypto has accumulated over the past decade-plus.
3. The Tether Investment Case
The crypto giant Tether's investment in NEURA Robotics is a typical case of this trend.
On June 10th, German robotics company NEURA Robotics completed a $1.4 billion funding round with investors including Tether, Amazon, Nvidia, Qualcomm, Bosch, Schaeffler, and the European Investment Bank, among others. NEURA stated that the funds will be used to scale the commercialization of cognitive robots and humanoid robots, with plans to produce millions of robots by 2030. The company also disclosed that its order backlog already exceeds $1 billion.
On the surface, this is an investment in AI robotics; but for Tether, it's clearly more than just a financial bet.
According to the related press release, NEURA's robot platform is expected to integrate Tether's Wallet Development Kit (WDK), embedding self-custody wallet functionality directly into the robot system. This means that robots in the future may receive micropayments for completing tasks, conduct transactions with other systems, or perform economic activities within human-preset parameters.
This is precisely one of the most imaginative new use cases for stablecoins.
In the past, the biggest users of stablecoins were traders, cross-border payment users, gray arbitrageurs, and some residents of emerging markets. It solved the problems of transfer, settlement, and value storage between humans. But if AI agents and robots begin to become economic actors, the usage frequency and scenarios for stablecoins could be significantly amplified.
A robot could accept orders, complete transportation, and receive USDT micropayments; an AI agent could automatically purchase data, invoke models, and pay for SaaS services; an automated supply chain system could automatically settle after goods arrive, sensors verify, and contracts confirm. Compared to traditional banking systems, on-chain payments are inherently suited for this high-frequency, small-amount, cross-border, machine-readable economic activity.
This is also why AI is not merely a competitive threat to crypto. AI is diverting crypto's capital attention, but it may also create the real demand that crypto has been lacking.
4. AI + Crypto is Not a Universal Formula
Of course, AI + Crypto does not inherently make sense.
Over the past two years, the market has seen too many crudely combined projects: connecting ChatGPT to a Telegram group is called an AI agent; packaging a model API call as token economics; cramming data annotation, computing power leasing, and agent platforms into a whitepaper. The problems with many of these projects are essentially no different from the last cycle's GameFi and SocialFi: big concept, small revenue, heavy tokenomics, light product.
Truly valuable AI + Crypto projects should meet at least one condition: they would not exist without crypto, or they are significantly better with crypto.
For example, agents need self-custody wallets and permission management; AI-generated content requires verifiable provenance and ownership; model, computing, and data markets need open settlement and incentive mechanisms; robot economies need machine-readable payment networks; autonomous organizations need transparent governance and enforceable rules. In these scenarios, crypto is not a marketing label slapped on the outside; it is a fundamental component required for the system to operate.
This is also the question crypto projects and VCs need to answer next.
If they simply change their fund intro pages to AI + Crypto just because it's easier to raise money, it won't change the industry's predicament. The market will eventually realize that most so-called integration projects have neither AI moats nor crypto necessity.
But if they can find the real intersection points in AI agents, robotics, data markets, financial automation, and on-chain identity, the crypto industry may indeed usher in a new application cycle.
This time, growth may not come from more retail investors rushing into exchanges to buy new coins, but from more machines, applications, and enterprises using on-chain rails in the background.
5. Conclusion
Faced with the impact of AI, the answer from crypto VCs is already clear: stop viewing crypto as an isolated vertical, but reinterpret it within larger technological waves.
This is both proactive evolution and a forced pivot.
When LP funds flow to AI, when entrepreneurs' attention flows to AI, when secondary market risk appetite flows to AI, crypto funds that continue to talk only about Layer1, DeFi, NFTs, crypto gaming, and airdrop growth will find their survival space increasingly narrow.
But this doesn't mean the crypto story is over. On the contrary, if AI agents truly become new internet users, if robots truly become new economic participants, and if automated systems truly begin to execute more and more transactions on behalf of humans, then the wallets, stablecoins, smart contracts, on-chain identities, and open financial networks built by crypto over many years may for the first time encounter high-frequency, essential, non-speculative use cases.
The crypto industry needs new narratives more than ever, but it needs new real demand even more.
