In the past year, the intersection of AI and cryptocurrency has become a hot area of consumer interest, driving the launch of numerous new projects.
Written by: Karen Shen
Compiled by: Block unicorn
In this article, we will explore the potential opportunities for collaboration between cryptocurrency and consumer-grade AI (artificial intelligence). This article is divided into three parts:
Why choose cryptocurrency x consumer-grade AI?
Overview of the traditional consumer-grade AI market
Opportunities in cryptocurrency x consumer-grade AI
Why choose cryptocurrency x consumer-grade AI
In the past year, the intersection of AI and cryptocurrency has become a hot area of consumer interest, driving the launch of numerous new projects. The vast majority of focus and capital has concentrated on the infrastructure layer of AI, such as computing power, training processes, inference techniques, intelligent agent models, and data infrastructure.
While many of these projects are ambitious and may deliver large-scale results, the technology has not yet reached production-grade levels (currently), and the likelihood of achieving widespread commercialization in the short term is low. This leaves a gap in the market for more directly impactful technological applications, particularly at the consumer-grade level.
Consumer-grade AI refers to AI products designed for everyday users rather than enterprise or business-specific applications. These products include AI-driven general assistants and recommendation systems, generation tools, and creative software. As AI technology rapidly advances, consumer-grade applications are becoming more intuitive, personalized, and easier for the average user to engage with.
Popular consumer-grade AI applications today
Unlike enterprise-grade AI, which typically requires precision and deterministic results, consumer-grade AI benefits from flexibility, creativity, and adaptability—areas where current AI excels.
Although still in its early stages, the combination of crypto technology and consumer-grade AI is undoubtedly a fascinating topic. It is rare for two technologies to progress towards maturity simultaneously, making it worth exploring—though predicting the outcome is challenging.
In the crypto technology space, there is an urgent need for more consumer-facing applications to provide new and interesting ways to interact with the underlying technology. Over the past decade, blockchain investment has driven significant advancements in infrastructure, including faster block generation times, lower gas fees, improved user experience (UX), and significantly reduced entry barriers that were common a few years ago.
You can intuitively feel how far the entire industry has progressed by simply trying to join applications like Moonshot, where you can use Apple Pay to instantly purchase meme coins. However, there is still a lack of founders and developers willing to tackle interesting consumer crypto problems.
Meanwhile, consumer-grade AI is market-ready, providing developers with a mature opportunity to combine these two technologies to build applications that shape the way we interact with, own, and engage with digital assets and AI systems.
Overview of the traditional consumer-grade AI market
First, let's use two resources to help us quickly understand the experiments within the traditional (non-crypto) consumer-grade AI space:
a16z's (top consumer products ranked by web traffic) (3rd edition)
The latest W24 project batch from the YC team
a16z's (top consumer products ranked by web traffic)
This report from a16z ranks the highest-traffic consumer-grade AI web pages and mobile applications every six months by analyzing web traffic data.
By analyzing this data, they identify how consumers are actively engaging with consumer-grade AI technologies, which categories are gaining attention, which are declining, and early leading projects within each category.
Here are the top 100 consumer-grade AI products as of August 2024, categorized by web and mobile applications.
Clearly, content generation and editing tools are leading the consumer-grade AI space.
These applications currently occupy 52% of the top 50 web apps and 36% of the top 50 mobile apps. Notably, this category is expanding from text generation to include video and music generation, further broadening the potential for AI-driven creative expression.
Popular categories such as general assistants, companion tools, and productivity tools have remained stable in the top 100 rankings, reflecting sustained demand. The third edition of the a16z report introduced a new category 'Aesthetics and Dating,' which saw three projects enter the rankings.
It is worth mentioning that a cross-category crypto project has also successfully made it onto the list. The anime companion app Yodayo (now Moescape AI) ranked 22nd on the web app chart.
Moescape AI
Comparing a16z's latest report with previous ones reveals that while the core categories of consumer-grade AI remain stable, about 30% of the top 100 projects are new, highlighting the ongoing evolution of this field.
The latest W24 project batch from the YC team
Next, let's review the latest W24 project batch from YC as a resource to help identify emerging consumer-grade AI projects and categories that, while they have entered the market, may not have enough appeal to appear in a16z's top 100 web traffic list.
The idea here is that while there is uncertainty about the actual demand from consumers for these products, this information can help us predict consumer-grade AI trends in the next 6-12 months.
Among the latest 235 projects, 63% focus on the AI domain, with 70% built on the application layer. Only about 14% of application layer projects are identified as consumer-centric.
Below is our attempt to categorize consumer-grade AI projects.
Similarly, content generation remains the most popular category among founders, with new projects continually pushing the boundaries of creative possibilities.
Similar to trends in the a16z report, the latest batch of YC entrepreneurs is exploring advanced content types, including storytelling, script-to-movie generation, music, video, and presentation-oriented content.
In addition to content generation, founders are also focused on search, productivity, and educational technology. These three categories are consistent with the a16z report, although most companies in YC are developing more targeted, vertically specific solutions in these areas.
Finally, categories such as gaming, automation, marketplaces, and streaming appear in this group, marking some new directions not seen in the a16z report.
Opportunities in cryptocurrency x consumer AI
Now that we have introduced the background trends in the traditional consumer-grade AI market, let's turn our attention to consumer-grade crypto AI.
First, we briefly introduce how AI can be useful for crypto products, or how crypto can be beneficial for consumer-grade AI products, which may be helpful.
Cryptocurrency and AI offer very different value propositions.
It can be argued that the values of these two technologies are at odds—cryptocurrency focuses on decentralization, privacy, and individual ownership, while AI tends to concentrate power and control in the hands of those who develop and own the most advanced models.
However, with the rise of decentralized and open-source AI, these boundaries are beginning to blur.
The core innovation of AI in consumer products is generating novel content that mimics and expands human creativity while learning from vast datasets, utilizing advanced neural network architectures to simulate complex relationships and produce high-quality outputs.
Early signs indicate that AI applications exhibit strong user retention and monetization potential. However, they also face a 'tourist problem,' where user traffic is high, but the conversion rate from free users to paid users is below usual.
On the other hand, crypto technology represents a design space that encompasses decentralization, crypto-economic incentives, and hyper-financialization characteristics. It is a distributed ledger that allows the value of any digital object to be stored in a transparent and traceable manner.
Crypto technology is highly effective in coordinating activities, aggregating decentralized infrastructure, and creating frictionless markets, allowing markets to be created easily where none existed before. However, aside from financial infrastructure, crypto technology has yet to create a compelling and sustainable consumer-grade application.
AI may be one of the key factors in unlocking the broader consumer potential of crypto technology. A recent study highlighted the rapid adoption of generative AI, which has surpassed that of PCs and the internet—with about 32% of U.S. residents using AI weekly. Given this pace of development, developers of crypto technology for consumer-grade applications who align their experiments and innovations with the accelerated adoption of AI will have a significant advantage.
We believe that through innovative consumer-grade applications that combine the powerful capabilities of AI with the unique advantages of decentralization and financialization provided by crypto technology, groundbreaking results will emerge.
Market Overview
The number of consumer-centric projects operating at the intersection of crypto and AI remains relatively low; our research estimates around 28, although this is not a final number.
In this crowdsourced decentralized AI market map, consumer-grade categories account for only about 13% of the total decentralized AI market, indicating significant room for growth. As a quick comparison, about 60-70% of products in the tech market are at the application layer, with about 70-80% being consumer-facing applications.
While we cover only a small portion of projects in this report, we were still able to identify some early insights.
We have identified some early insights from teams integrating crypto with AI. These insights have been distilled into several broader use cases, some of which show potential while others may be less sustainable.
Incentive Mechanisms: Cryptocurrency serves as an incentive and rewards users for activities on AI platforms/apps. For example, one use of Wayfinder's native token is to reward agents and participants for creating valuable on-chain paths as AI agents traverse the chain. For Botto, the automated AI artist requires its community to provide feedback on its art creations. Botto rewards this participation by distributing a portion of its art sales in the form of $BOTTO tokens.
Financialization: The ability to trade, own, and generate income from AI assets on the blockchain. For instance, Virtuals Protocol provides a platform where anyone can purchase and own a portion of AI agents and benefit from the income generated by the AI agents they trust. Ownership is represented in the form of tokens.
Attribution: Allowing IP holders to track, verify, and claim royalties on the blockchain. For example, uncensored companion projects like Oh.xyz are using cryptographic technology to create digital twin NFTs for creators on their platform to verify content authenticity and claim royalties in the future.
In-app or in-game economy: Cryptocurrency as in-app/in-game currency. For instance, games like Parallel and Today will have in-game economies where players and their AI agents can trade resources using their respective tokens.
Decentralization: Decentralized networks, services, and models. For example, BitMind is a subnet on Bittensor that is building the first decentralized deepfake detection system. By leveraging Bittensor, they can encourage open competition among AI developers to contribute towards building the best deepfake detection model.
Anti-censorship: Removing censorship from generative AI content creation. For example, Venice is a private and permissionless generative AI assistant that is built on Morpheus's decentralized universal agent network. Unlike traditional AI assistants, Venice does not censor AI-generated content or download your conversations.
Membership System: Cryptocurrency as a means to access premium features. For instance, MyShell's ecosystem token has multiple use cases, one of which is to grant holders access to premium features.
Assistant: AI is a way to facilitate interactions between people and cryptocurrency. For example, Wayfinder, Fere AI, Fungi, and PAAL AI are vertical general assistants or bots tailored for the cryptocurrency industry, aimed at making the end-user's crypto experience more convenient.
Contextualization: AI is a way to contextualize and personalize content on the blockchain. For example, Unofficial aims to build a discovery engine for on-chain socialization using zkTLS and RAG on Farcaster.
After examining the current cryptocurrency and consumer AI markets—including the applications of cryptocurrency and AI, as well as the state of established and emerging categories in the traditional consumer-grade AI space—the next section will explore the most promising design spaces in this intersection for developers' reference.
Games and agents/companions
There are reasons why games and agents/companions have become the two most popular categories for founders in this intersection. They provide the most suitable environment for AI and cryptocurrency experimentation.
Games and agents typically operate in fictional realms with the aim of entertaining consumers. Their outcomes often do not need to be deterministic and usually have minimal real-life consequences. Thus, this provides perfect conditions for experimentation.
Today's surreal gaming environments
So far, games like Parallel Colony and Today have used AI as the core experience of the product, where AI NPC characters in games behave like real humans, exhibiting autonomy and the ability to converse.
Cryptocurrency is being used as a financial channel for in-game payments, agent-to-agent payments, or unlocking character ownership.
It is crucial that this new digital economy represents an advantage of these crypto games over the many AI games that are about to launch.
AI is a transformative technology that will undoubtedly be a key part of future game development and gaming experiences—but we believe that teams building AI games targeting the digital native economy will have the greatest competitive advantage.
AI agents in games are interesting, but what cryptocurrency unlocks is the ability to introduce an economic system that replicates human experiences for the first time in games. NPCs in games cannot open their own bank accounts, trade, or make real economic decisions. As a result, many unprecedented behaviors and opportunities may arise.
As Kalos, the founder of Parallel, said on Twitter:
Today, this is best exemplified in fictional environments like gaming.
Projects building AI agents and companions share similarities when using AI and cryptocurrency—AI as the core experience, and cryptocurrency as the financial infrastructure. However, unlike agents in games that operate within a limited environment, allowing for more complex interactions with minimal real-life consequences, agents and companions currently are limited to one-on-one or one-to-many relationships.
For example, using MyShell, Virtuals Protocol, or MoeMate, end users interact with AI chatbots through chat or voice features—interactions are limited to you and the chatbot (or other medium). Chatbots are LLM wrappers with limited attributes that can be customized by the creators of the bots, such as the tone of communication, the appearance of the agent, etc. Thus, your interaction with these chatbots is also limited in creativity.
The experience of MoeMate's Draco Malfoy AI chatbot
Although similar to its competitors, ai16z takes an open-source, bottom-up approach focused on building on-chain AI agent infrastructure, providing tools for the future of multi-agent interactions.
In the realms of gaming and agents, there are still many areas worth exploring, such as multi-agent experiences or infinite game modes. Consumer experiences involving many-to-many AI agents interacting with humans may be complex but could yield more dynamic, engaging interactions and more intricate crypto economic systems. This area has yet to be fully explored outside of gaming environments.
We still believe this is one of the areas most interesting to founders, and we can't wait to see what innovations the future will bring.
General assistants and content generation tools
General assistants and content generation tools dominate the traditional consumer-grade AI space. However, fierce competition makes entering this market challenging and costly, which also explains why these categories are not as strongly represented in the crypto market map as they are in traditional AI.
Nevertheless, the demand for these tools remains strong, consistently ranking high in a16z's web traffic analysis. For founders in the intersection of crypto and AI, these categories still hold promise, especially for products tailored specifically for crypto users. By focusing on the unique needs of the crypto space, there is potential to create unique value without competing in a saturated traditional market.
Here are some examples:
Supporting AI with crypto assistants: It is well-known that crypto can be difficult to navigate. Whether you're trying to buy or swap tokens on-chain or meet the conditions required to participate in gaming or social experiences, there are many obstacles.
Are you on the right network? How to switch networks? Do you have the correct Gas tokens? How to transfer funds to the target network?
For newcomers, the learning curve is steep. Even for those familiar with cryptocurrencies, these tasks may still take a significant amount of time.
While the industry has mainly improved in account abstraction, intents, and other UI/UX aspects so far, AI is more likely to integrate these developments and push these transformations forward. Some teams like Wayfinder, Fungi, PAAL AI, and Fere AI are already exploring solutions, although no team has yet made significant progress—leaving room for more competitors and specialization.
Overview of Wayfinder's crypto assistant
The demand for experienced Solidity developers may differ from that of newcomers. We believe that teams that consider specific user groups (tailoring the experience entirely based on the volume of questions for that user group), provide refined user experiences (leveraging advancements in account abstraction and intents), and offer personalized services (based on users' past on-chain activities) are most likely to succeed.
Asset generation supported by AI: In the crypto space, content generation can be viewed as asset generation. These assets can be tokens and digital assets in forms such as ERC20, ERC721, ERC1155, or other standards, with nearly limitless ways to generate them. Similar to how Midjourney and DALL-E generate images, or how SUNO creates music, AI can also play a key role in generating crypto assets.
Examples of early-stage AI-driven crypto asset generation include Truth Terminal's $GOAT token, Wayfinder's asset deployment agents, Swan's upcoming gamified asset generation market, and Virtuals Protocol's AI agent launch platform.
In addition to asset generation, AI can also shape narratives, marketing assets, and give them 'voice.' For specific asset types like meme coins (which have no external dependencies), AI can efficiently streamline the end-to-end asset development process.
In a world where AI agents can effortlessly generate countless crypto assets, the opportunity for developers lies in identifying the flow of value and attention. For example, the strategy taken by Virtuals Protocol is to shift speculative behavior to the creator level, allowing consumers to predict the ability of AI agents to attract attention and create interesting assets.
We are currently in the early stages of a crazy new reality where AI can generate real financial value in the form of crypto assets, and humans can enjoy and speculate on the development of these assets. While the future of this trend is unpredictable, this space offers vast experimental opportunities, and we will closely monitor its direction.
Miscellaneous
There are still many categories in the intersection of crypto and consumer-grade AI that have not been fully explored. With the rapid development of AI, these categories are likely to grow and evolve rapidly. While many categories may be ephemeral, and those suited for crypto collaboration may be fewer, there is still ample room for experimentation in this field—we welcome that!
One way to think about it is to consider crypto equivalents of traditional consumer-grade AI projects, especially those that currently have no intersection with crypto. For example, we applied crypto technology to two categories in the a16z and YC lists and added an additional category for exploration.
Educational technology (Edtech) is a popular consumer-grade AI category that can benefit from various layers of the stack through crypto technology. Education covers areas, subjects, languages, education levels, and teaching methods. In this case, rather than taking a centralized approach, it’s better to advance educational technology through open-source development in collaboration with global contributors. In this context, an education-focused subnet on Bittensor can help build these models.
Cryptographic technology can also be applied to the incentive layer of educational technology (Edtech) applications. Beyond traditional gamification strategies (such as Duolingo's daily streak mechanism), with crypto technology, teachers and students can be rewarded for their contributions and efforts on both the supply and demand sides.
For self-service, the potential of cryptocurrency in achieving data ownership and monetization could be significant. Due to various reasons such as cost, social stigma, lack of awareness, and a shortage of professionals, it remains difficult for many to access. Projects like Sonia and Maia (both recently incubated in the latest YC batch) have preliminarily demonstrated the feasibility of affordable AI-driven mental health counseling solutions. Traditionally, therapists' notes are stored in paper or digital files in their offices, making data inaccessible. However, for AI therapists, data can be stored privately online, unlocking entirely new use cases from individuals' mental health data.
Imagine if you could truly own the data from AI therapy sessions. You could choose to keep it private, monetize it, or even anonymously contribute it to a health data network to support meaningful research. Crypto-native projects like Vana are making this possible, allowing people to have stakes in their own data.
In the entertainment sector, projects like Unlonely are attempting crypto-native live streaming, where users can speculate and influence the outcome of live streams through the tokens of a trading platform. Currently, this is limited to real-world events, but it could extend to AI-generated content. This could enable 24/7 live streaming, giving users greater control over the narrative. MineTard AI is a recent early example. It is an AI agent that live-streams Minecraft 24/7 on Kick, and the agent can be influenced by $MTard holders.
Last year, a viral trend emerged on TikTok where creators played NPCs, performing specific actions based on the 'gifts' they received. While this content type is fleeting, it clearly indicates consumer interest in interactive live experiences. With advancements in AI-driven NPC technology, similar gamified interactions may fit crypto-native live streaming, where AI NPCs can respond in real-time to user inputs.
Trending NPC phenomena on TikTok
These are just some rough ideas on how to apply crypto and AI to consumer-grade applications. In this report, we have not covered all possible applications, and we expect more such innovations to emerge as the industry rapidly evolves.
Message
You may have already noticed that we are very excited about the potential at the intersection of crypto and consumer-grade AI. The projects currently being built in this space represent only a small fraction of the possibilities.
With the parallel development of these two technologies, founders have a unique window to create a new wave of consumer-grade applications that could change the way we interact with and participate in digital assets and synthetic intelligence.
For those building in this space, we encourage you to continue pushing boundaries and explore unconventional applications of these technologies. We also hope that for some, this resource can aid them on their journey.