The 0xScope Crypto + AI Industry Map

Crypto and Artificial intelligence (AI) are two of the most groundbreaking technologies that have emerged into the mainstream in recent years.

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AI is changing the way we seek information and leverage about the world. Over the past two years, we've seen the quick ascent of ChatGPT as a major force in AI, with over 180 million monthly users and a slate of emerging competitors from tech giants such as Google.

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Meanwhile, the Web3 industry has also made great strides in reshaping how we approach money, trust, and innovation, among many others. Cryptocurrencies transformed our relationship with value, presenting decentralized alternatives and opportunities to traditional financial systems.

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Hence, there has been great interest in combining the two to develop the next wave of tech innovation. In this article, we'll discuss the current landscape of the crypto + AI intersection, the goals and challenges being addressed, and 0xScope's role in unlocking further evolution in the space.

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The Crypto + AI Market

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Understanding the crypto + AI market is a rapidly evolving endeavor, given that this industry is just a few years old. Industry experts from both the crypto and AI fields, including our own research and development team, are currently deliberating on the right methods of assessing the crypto + AI market's classifications, valuations, and other metrics. Here, the 0xScope team presents three possible interpretations.

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Crypto + AI Token Market Cap

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According to Scopechat, which is in itself a Web3 + AI product for crypto trading intelligence, 136 cryptocurrencies are currently associated with AI-related projects and solutions. The combined market cap for all these tokens is $17.86B. AI-affiliated crypto tokens have been on the rise in recent weeks, with a 7-day average growth of 9.5% as of February 28, 2024. It's important to note that these tokens' associations with crypto + AI solutions may vary, with some tokens likely riding the momentum of the Web3 AI narrative.

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To learn more about these tokens and the AI narrative in crypto, you can try Scopechat here or check this sneak peek of the answer from the AI-powered crypto trading assistant:

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Crypto + AI Industry Valuation

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While the token market caps of crypto AI companies can be used to assess the market's health, we can also derive some further understanding from traditional financial analysis. After all, the AI industry is still largely evaluated under this framework.

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The crypto + AI market was estimated to be worth $220.5M in 2020 and is expected to grow to $973.6M by 2027, according to the financial research firm Fortune Business Insights. This represents a compound annual growth rate (CAGR) of 23.6%. However, the 0xScope team thinks that this estimate is quite conservative, given the current valuations of crypto and AI industries.

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For instance, the Generative AI market is estimated to grow from just $40B in 2022 to $1.3T by 2032, at a CAGR of 42%, according to Bloomberg Intelligence, while rising demand for generative AI products could add about $280 billion of new software revenue. Two years removed from 2022, AI market leader OpenAI's valuation reached $80B, representing 3x growth over the past 10 months, after a recent tender offer led by Thrive Capital. Meanwhile, the crypto market in itself is at a growth trajectory, recently returning to $2.2T in total market cap after rising from just $800B at the start of 2023, with a fair chance of surpassing its $2.8T height from back in late 2021.

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Therefore, depending on how well crypto converges with AI, the crypto + AI industry will likely lean closer to the range of tens of billions of dollars. After all, as you'll see later in this article, some of the Web3 companies that are actively working on crypto + AI are already valued in the billions.

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Crypto + AI Ecosystem: Classifications and Valuations

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Categorization among crypto + AI companies helps us understand their core competencies and gives us a glimpse of their potential growth trajectories. For instance, in a recent article about the convergence of crypto and AI, Ethereum founder Vitalik Buterin identified the four most apparent roles for crypto + AI companies. Here, we provide a brief interpretation of the four roles:

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1. AI as a player - AI technology applied in Web3 solutions on a tool-level capacity, such as AI-powered trading bots and prediction market participants

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2. AI as an interface - At this level, AI is leveraged in a user-facing capacity for Web3 interfaces; in some instances, these platforms act as micro-markets for AI-powered tools, agents, and users.

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3. AI as the "rules of the game" - Web3 projects approach AI technology as a core component of the protocols, DAOs, and Web3 infrastructure they build, going beyond tool- and interface-level applications for AI.

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4. AI as the "objective" - Web3 projects apply AI technology for utilities that encompass or even go beyond entire blockchains.

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Here, we can observe the four different pathways that crypto + AI companies are pursuing, differentiated based on how they intend to use AI for their Web3 platforms. Applying this logic to the current crypto + AI industry landscape, we can distinguish which companies are focused on tools and apps, on interfaces/marketplaces, on protocols and Web3 infrastructure, or on entire blockchains for integrating AI solutions.

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For this report on crypto + AI, we have identified the four main categories for companies in the space:

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1. Tools and Apps (AI as a player)

2. Interfaces and Marketplaces (AI as an interface)

3. Infrastructure and Protocols (AI as the "rules of the game")

4. Blockchains and Ecosystems (AI as the "objective")

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Before discussing these categories, we shall provide an overview of the crypto + AI ecosystem, which currently consists of at least 138 Web3 companies that are actively developing AI products, platforms, and more, whether as their core product or a major component of their ecosystem. This sector has a total market cap of at least $18.44B and a combined fundraise worth $1.24B from venture capital and other avenues.

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Click here to zoom into the image.

Source: 0xScope, RootData

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Please note that these figures are likely conservative, given that just 41 of these companies have disclosed their fundraising details. Meanwhile, 41 companies have their own tokens, only 28 of which have circulating market cap figures. These 41 companies with crypto tokens have a combined fully diluted valuation of $36.4B, but for the purposes of this report, we will lean more towards market caps and fundraises. Also, as crypto AI is a rapidly evolving space, some companies may not be included in this infographic. We will update this map to reflect companies that warrant inclusion; please reach out to us via email at community@0xScope.com for more details.

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We now focus on the four categories and what makes each of them different.

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1. Crypto + AI Tools and Apps

Companies under this category mainly focus on creating dapps and tools that use AI to delive specific digital products and services, such as AI-enhanced NFTs, AI-powered social networks, automated chatbots, and more. In this instance, AI is used as a tool to advance towards a crypto- or product-related incentive through surface-level application on a simple product-to-customer level.

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This category makes up the majority of the crypto AI ecosystem, given that this is the easiest path towards incorporating AI into Web3. Companies that lean towards this role are focused on building dapps that use AI to enhance their specific services, from generative AI for NFTs to trading chatbots. This is the area where AI integration in Web3 is most visible, although these AI-powered dapps tend to target narrow niches.

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The 79 companies under this category have raised at least $693.4M in funds, while their tokens have a cumulative market cap of $4.86B.

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2. Crypto + AI Interfaces and Marketplaces

Companies under this category often act as marketplaces for AI services and datasets, while others act as interfaces where their communities can collaborate on their own AI-supported Web3 apps.

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While these companies' marketplace-oriented business models incentivize developers to build and sell their own AI-powered services, this setup tends to promote a more fragmented lineup of products that can be challenging to scale or standardize. Nonetheless, AI integration for these companies is more in-depth, as it involves transactions between AI agents or services and customers.

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The 17 companies under this category have raised at least $108.5M in funds, while their tokens have a cumulative market cap of $1.43B.

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3. Crypto + AI Infrastructure and Protocols

In this category, companies focus on AI integration within protocols, Layer-2 platforms, and other back-end solutions. Examples of this include the creation of decentralized infrastructure for training AI models.

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These companies tend to have products that are geared towards organization-level clients, such as projects, DAOs, and other business-related customers. Their focus on bigger-scale solutions would make them unlikely to focus on more granular solutions that can fast-track Web3's AI integration. Nonethless, the work these companies do are crucial for empowering other projects to come up with their own AI-powered dapps.

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This niche mainly deals with the use of "AI judges" that can help make decisions on a smart contract or DAO level. Vitalik said that this aspect of crypto AI integration is the most risky, due to challenges related to efficiency and security.

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The 34 companies under this category have raised at least $372.1M in funds, while their tokens have a cumulative market cap of $6.99B.

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4. Crypto + AI Blockchains and Ecosystems

Web3 companies that are under this category deal with big-picture solutions such as the integration of AI into entire blockchains and frameworks. What makes these companies different from those that work on crypto AI infrastructure and protocols is mainly the scope of AI integration, which goes beyond specific protocols. This is where companies attempt a comprehensive use of AI as the core component for building their own networks.

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Understandably, there are only a few companies in this category at the moment. However, we anticipate a steady increase in the number of Web3 projects that will work on this level of AI integration, whether it's a new startup or a more established company that is pivoting towards this direction.

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The 8 companies under this category have raised at least $61.5M in funds, while their tokens have a cumulative market cap of $5.16B.

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Challenges Facing Crypto + AI Companies

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Regardless of the level of AI integration in Web3 apps, companies in the crypto AI space face an inherent problem concerning Web3 data. The decentralized nature of Web3 has resulted in a major problem: crypto data still lacks standardization, despite the best efforts of the industry's many brilliant developers.

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Right now, the Web3 industry relies on APIs and oracles to provide timely and accurate information that dapps can act upon. A few Web3 projects, such as Chainlink, have emerged as vaunted institutions for data transmission and processing. Chainlink's unique value proposition is its capability to facilitate the transfer of tamper-proof data from off-chain sources to on-chain smart contracts, a valuable service for many of the biggest decentralized apps (dapps) in the Web3 space. However, the development of AI requires higher-quality data that can't simply be addressed by oracles, at least in their current forms.

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Therefore, the next evolution for Web3 + AI integration is the creation of a reliable data layer that crypto AI companies can use for their solutions. This is the space where 0xScope, a Web3 company that has made its mark in the industry through its data analytics solutions, will play a major role, specifically through the 0xScope Web3 AI Data Layer.

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The 0xScope Web3 AI Data Layer as a Core Catalyst for Crypto + AI Growth

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0xScope is the first Web3 AI Data Layer with an established and complete set of standards for collecting, cleaning, and managing relevant on- and off-chain data specifically adapted for Web3 AI training. With 0xScope, developers can quickly obtain high-quality data and use it for training and optimization of AI-powered decentralized apps. At the same time, 0xScope has trained a Web3-centric large language model (LLM) that is based on the 0xScope data layer and is further enriched through continuous iteration. Developers can directly train Web3 AI agents based on this model.

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Stemming from its Web3 data analytics roots, 0xScope has done an enormous amount of prior preparation concerning the collection, processing, and presentation of Web3 data from some of the most respected names in the crypto space. At the same time, 0xScope's data analytics tools have done most of the heavy lifting for the refinement and association of Web3 data, including the company's proprietary system of identifying real users from multiple Web3 addresses. The work that 0xScope has done on that front has vastly improved the quality of Web3 data that can be provided to developers, while greatly reducing the amount of data noise that can hinder the development of AI-powered Web3 solutions.

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In other words, 0xScope combined its vast experience in standardizing and filtering Web3 data with AI integration to create the ideal data layer for crypto AI companies, which stand to benefit from the following:

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- Access to a large AI-powered industry model for Web3

- A better understanding of Web3 user intent, allowing for enhanced targeting and refinement of services for the right audiences

- Various new forms of interaction with Web3-native AI products

- A unified standard for Web3 data, powered by different manufacturers and developers who independently submit data that 0xScope processes into more actionable insights

- Access to 0xScope's accumulated high-quality data, driving the creation of highly-developed showcase products and large industry models.

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Here's an illustration of the role that 0xScope's Web3 AI Data Layer plays in the progress of crypto + AI:

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0xScope is already using its Web3 AI Data Layer to create new AI-powered solutions, like the Scopechat crypto trading assistant.

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A Case Study on Scopechat: The 0xScope Web3 AI Data Layer in Action

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Scopechat, is an easy-to-use, intuitive, AI-powered assistant for crypto traders and users of all levels, from beginner to expert. This app, powered by the 0xScope Web3 AI Data Layer, leverages public and proprietary data sets to deliver accurate, comprehensive answers to any Web3-related questions you type in.

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During the development of Scopechat, 0xScope curated an AI-assisted user experience that leverages its wide coverage, high-quality data warehouse, AI-driven algorithm, and LLM technology. 0xScope introduced various modes and features to Scopechat that help users get their answers more conveniently. Through the combination of user-generated feedback loops, 0xScope’s proactive enhancements, and the self-training inherent in the Web3 AI Data Layer, Scopechat was able to refine its core features and deliver better results.

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What sets Scopechat apart from AI-powered crypto assistants in the market is the higher quality and sophistication of Web3 datasets that it uses. Through the 0xScope Web3 AI Data Layer, Scopechat leverages information from several Web3 data sources, including advanced Web3 data analytics from Scopescan, among many others.

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Here's a quick comparison of the capabilities of Scopechat versus other AI-powered crypto assistants. For more details, please check this recent article about Scopechat and other industry players in this particular niche.

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In just two months since its beta launch, Scopechat has been able to deliver more sophisticated crypto trading reports, including recent updates such as enhancements for refining AI-generated answers and a token alert system, the first of its kind in the crypto + AI space, that notifies users of abnormal on- and off-chain activities as they happen.

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Try Scopechat today.

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Case Study: Integrating the 0xScope Web3 AI Data Layer to Make Smarter Crypto Wallets

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Crypto + AI is not only about creating new products and solutions. A valuable case for leveraging a Web3 AI data layer like 0xScope is the potential to enhance existing dapps. Web3 has made great strides in making its services more user-friendly and loaded with useful features. Adding an AI-powered component, powered by the 0xScope Web3 AI Data Layer, can take these apps to the next level by giving them unique advantages compared to their competition.

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For instance, an existing crypto wallet can further enrich its user experience and give its customers more reason for regular use with the help of AI-powered features. Here are some examples:

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- A crypto wallet can increase its trading volume by incorporating AI-powered token ranking dashboards, chatbots, and other interfaces that help users find their next trading opportunities. If a crypto wallet can provide this trading alpha to users within the dapp itself, it can potentially see boosts in usage, screen time, and other important metrics.

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- Crypto wallets regularly interact with other dapps, both legitimate and suspicious. One feature that will prove beneficial for user convenience and security is an AI-powered plugin that helps crypto wallet users get information about the projects they connect with. The Web3 AI data layer takes care of providing this timely information, all within the comfort of the wallet.

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- Another use for an AI-powered filtering system within a crypto wallet is the capability to check the on-chain activity of the addresses that a user may interact with. A user can check an address' transaction history, money flows, and other important information without needing to go to a block explorer outside of the app. This system can also proactively warn users if an address is likely involved in fraudulent activity, increasing the crypto wallet's safety in the process.

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Where is Crypto + AI Headed?

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Scopechat is just one of the hundreds of AI-driven concepts in the Web3 industry. As both blockchains and AI solutions rapidly advance, there are hundreds more applications that may emerge in the convergence of these two technologies.

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However, it's quite clear that crypto + AI would take a few more years before being able to develop apps that are suitable for widespread use, especially given that much of the work that's being done in the sector is mostly on infrastructure and specific tools. Most of the public-facing AI-powered crypto solutions are more exploratory or proof-of-concept in nature, and the companies behind them are still at the early stages of defining these services' value propositions, according to a recent study on crypto + AI by Web3 investment firm Galaxy.

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Here are some of the possible trends that we can see at the intersection of Web3 and AI:

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1. Higher Democratization of Web3 Platforms

AI can democratize the intricate world of Web3 and grow the market for the entire crypto industry. Some of the notable hindrances to Web3's further growth have been linked with its lack of user-friendliness, especially for those who are just starting with crypto. AI solutions that are crafted for Web3 use are well-positioned to enhance the crypto experience with higher efficiency, allowing developers to spend less time on tasks that would have been time-consuming without AI, among many other advantages.

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2. AI-Powered Crypto Security and Privacy Solutions

Web3's security problems are multi-faceted, from platform-related issues to user-focused attacks. Applying AI's predictive analysis and machine learning capabilities to Web3 can result in more robust solutions for fraud prevention, security patches, threat mitigation, and many others.

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"Crypto is already being used as a means of verifying the authenticity and combatting increasing amount of AI generated/manipulated content and deep fakes," according to Galaxy, which added that innovations like zero-knowledge Machine Learning (zkML) can accelerate the progress of crypto-native security.

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3. AI-Optimized Smart Contracts, Governance Protocols, and Personalization

Since ChatGPT became popular, many developers have taken advantage of AI technology to automate and optimize smart contracts, DAOs, and other Web3 systems, raising the quality of the functions being created for crypto. In addition, AI can unlock novel ways to fine-tune dapps based on a user's tendencies and preferences, while addressing privacy concerns related to these enhancements.

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And it's not just AI that can enhance crypto solutions. Also currently being explored are the possibilities of using crypto data to enhance machine learning, especially in fast-moving sectors like DeFi. Galaxy noted, "DeFi protocols provide machine learning models with large amounts of verifiable and immutable data that can be used to generate yield generating or trading strategies, risk analysis, UX, and much more."

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4. Decentralized AI Models

With the development of more powerful blockchains that can support sophisticated AI solutions, the fusion of these two technologies can transcend beyond niche applications and ultimately become more integrated into blockchain platforms themselves. However, this particular development can be one of the more complicated aspects of integrating AI into Web3. "The most challenging [thing] to get right are applications that attempt to use blockchains and cryptographic techniques to create a 'singleton': a single decentralized trusted AI that some application would rely on for some purpose," Vitalik said in his article.

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Ultimately, the most important participants in shaping the future of crypto + AI are the companies, projects, and other entities that have already made significant progress in building their AI-powered solutions. Crypto AI companies today have a first-mover advantage in exploring more utilities for AI-powered services.

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For example, the 0xScope Web3 AI Data Layer can be integrated into traditional crypto information dapps to unlock novel ways to present Web3 data based on user traffic and behaviors. Users who now check multiple platforms to look for signals will be able to do it simply on a dapp that leverages the Web3 AI data layer and at a fraction of the time, giving that platform a unique advantage in an increasingly competitive field. The possibilities unlocked by AI integration in Web3 will depend on the entrepreneurial spirit and creativity of crypto AI proponents.

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Conclusion: How to Work Together Towards a Better Web3 AI Landscape

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The 0xScope Web3 AI Data Layer solves many problems that Web3 projects face regarding the creation of AI-powered solutions. Web3 developers can construct large AI industry models for their dapps by sourcing data in one place only, being reassured about the accuracy of such data. Web3 services can quickly understand user intent, greatly reducing the amount of time and resources spent on targeting the right audience and allowing Web3 projects to focus more on refining the value of their existing solutions. In addition, various new forms of Web3 interactions and Web3-native AI products will become possible.

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As part of its future plans to enhance its Web3 AI Data Layer, 0xScope is also building an economic system wherein any contribution of small and medium-sized developers and data analysts can be rewarded with a unified standard. Through this system, the 0xScope Web3 AI Data Layer will expand to facilitate a more cohesive collaboration between data providers, platform developers, data quality checkers, node services, data purchasers, and other participants in the crypto information economy.

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To take advantage of the 0xScope Web3 AI Data Layer and be at the forefront of crypto + AI innovation, you can reach out to community@0xscope.com.

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