The total market capitalization of the crypto AI asset sector has surpassed $70 billion this year, with the number of related projects exceeding 600.
Article author: Xiyou
Source: ChainCatcher
In 2024, the 'Crypto+AI' (crypto AI) field achieved unprecedented breakthrough growth. At the beginning of the year, this field was only composed of a few scattered projects, but now it has become an independent track in the crypto market that cannot be ignored.
According to the latest data compiled by ChainCatcher, as of December 7, the total market capitalization of the crypto AI sector has surpassed $70 billion, accounting for up to 2% of the entire crypto market, with an annual growth rate of 400%.
At the same time, the number of crypto AI projects has also exploded, now exceeding 600, covering multiple categories of decentralized AI infrastructure, AI Dapps, and more.
Looking back at 2024, the narrative of crypto AI experienced several significant changes. At the beginning of the year, OpenAI's launch of the Sora project ignited a speculative frenzy around crypto AI infrastructure. Subsequently, the annual AI conference hosted by Nvidia brought decentralized GPUs into the market spotlight, leading investors to flock to AI decentralized infrastructure. In the middle of the year, the crypto AI track experienced an investment boom, with crypto VC institutions announcing their involvement, and many crypto projects receiving funding support, accelerating the technological development and application process. By the end of the year, the explosion of AI Agent Meme pushed the narrative of crypto AI to a new climax.
The total market capitalization of crypto AI assets has surpassed $70 billion this year, with the number of related projects exceeding 600.
According to the latest data from CoinMarketCap, the number of tokens in the crypto artificial intelligence (Crypto*AI) sector has reached 355, with a total market capitalization exceeding $70 billion on December 7, peaking at $70.42 billion. Currently, due to the overall downward trend in the crypto market, as of December 23, the total market capitalization of the crypto AI sector has fallen to $47 billion, with a 24-hour trading volume still high at $5 billion.
Looking back at the beginning of the year, the total market capitalization of the crypto AI sector was only $17 billion. In less than a year, the total market capitalization of this sector has achieved an increase of over 400%, once again showcasing the robust development and immense potential of the crypto AI field.
Daniel Cheung, co-founder of Syncracy Capital, expressed his views on December 12, pointing out that although the current crypto AI sector only accounts for about 1% of the total market capitalization of the crypto market, with the continuous evolution of market cycles and the robust momentum of AI infrastructure and AI Agents, he predicts that the market capitalization of this sector could achieve a tenfold increase.
It is worth mentioning that despite the overall retreat of the current crypto market, on December 23, the total market capitalization of the entire crypto market reached $3.4 trillion, while the market capitalization of crypto AI assets still accounted for nearly 1.4% of the entire market at that time (over 2% during market capitalization peaks), further proving its future market growth potential.
2024 is a pivotal turning point for the crypto AI field, transitioning from emerging prominence to full-scale explosion. At the beginning of the year, the crypto AI track was still in its infancy, with only a few projects, mainly represented by decentralized GPU projects like Render (RNDR), AI infrastructure like Fetch.ai (FET), and WorldCoin. However, in less than a year, the crypto AI field has been subdivided into multiple niches, covering decentralized GPUs, AI data platforms, AI infrastructure, and AI Agents, with hundreds of projects.
According to data from the crypto data platform Rootdata, the number of crypto projects containing AI entries has exceeded 600, and this number continues to increase.
Crypto AI Catalysts in 2024: OpenAI narrative and other external forces, heavy VC layouts, explosive growth of AI Agent Meme.
From the data trend of the total market capitalization of crypto AI assets, the growth in 2024 shows two significant peaks: the first peak occurred between February and March, while the second occurred after October, welcoming a stronger wave of growth.
During the period from February to March, the growth of the crypto AI field was mainly driven by two landmark events in the AI sector.
In February, OpenAI shockingly released the 'Sora' large model for video generation, which initiated a disruptive transformation in the AI field. At the same time, this event also greatly boosted the price of the WLD token of the iris authentication crypto project Worldcoin, led by OpenAI founder Sam Altman, subsequently driving strong growth in the entire crypto AI asset sector. During this period, high-quality projects such as the AI model incentive platform Bittensor (TAO) and the AI data platform Arkham's ARKM began to receive widespread market attention, as the rise of these projects further fueled investment enthusiasm in the crypto AI market, attracting a large influx of investors into this promising emerging field.
Following that, the grand opening of Nvidia's annual AI conference GTC in March attracted widespread global attention once again, pushing its market value to soar and triggering a GPU chip speculation frenzy. At the conference, prominent figures from the crypto industry, such as Near co-founder Illia Polosukhin and Render Network founder Jules Urbach, injected new vitality into the crypto AI field. This series of events led to the emergence of concepts like decentralized GPUs, with projects like the once-popular decentralized io.net being founded at this time.
Thus, crypto AI has officially developed into an independent track, with projects like AI infrastructure, decentralized GPUs, and decentralized AI data emerging in droves, bringing more choices and opportunities to the market.
In October, the growth in the crypto AI field was mainly attributed to the explosive rise of AI Agent Meme. The launch of the AI Agent project Truth Terminal's token GOAT sparked a speculative frenzy around AI Agent Meme projects, leading to the batch issuance of nearly a hundred AI Agent Meme coins. This trend has led to the rapid rise of AI Agents, becoming an independent niche track within the crypto AI field, with products including AI Agent Meme coins, AI Agent issuance platforms (IAO), and AI Agent underlying infrastructure, with specific projects detailed in ChainCatcher's November report (Systematic Overview of the AI Agent Track: AI Meme, Issuance Platforms, and Infrastructure). According to Coingecko data, as of December 23, the total market capitalization of tokens in the AI Agent track has reached $9.8 billion, accounting for about 20% of the total market capitalization of the entire crypto AI track ($47 billion), and the speculative heat is still ongoing.
If the external strong drivers for the development of the crypto AI field include the launch of OpenAI's Sora video generation tool, the rise in Nvidia's market value, and its AI summit, then the explosive growth of AI Agent Meme is undoubtedly a fire ignited from within the crypto market, accelerating the rise of this field. Under the combined effect of internal and external dual catalysts, the crypto AI track has rapidly become a key area in the crypto world that cannot be ignored, with its importance becoming increasingly significant.
Furthermore, in 2024, the crypto AI market welcomed an unprecedented investment boom, with major investment institutions rushing in, and investment amounts skyrocketing. In this field, top venture capital institutions in the crypto industry, such as Grayscale, Delphi Venture, Coinbase Ventures, Binance Labs, and a16z, have actively laid out 'Crypto+AI' projects.
At the beginning of the year, Delphi Ventures expressed high optimism about the combination of Crypto and AI, investing in several related projects such as io.net, OG Labs, and Mythos Ventures. a16z raised a new $6 billion fund, focusing on investing in the AI field, and selected 5 crypto AI projects in its autumn crypto startup accelerator. Entering the second half of the year, institutions such as Pantera Capital, Grayscale, Binance Labs, and Coinbase Ventures announced their entry into the crypto AI field, setting up dedicated funds or increasing investment intensity. According to a report released by Messari, crypto venture capital institutions injected over $213 million into AI projects in the third quarter of 2024, a month-on-month increase of 250% and a year-on-year increase of as much as 340%.
'Crypto for AI' has greater market prospects than 'AI for Crypto'.
Currently, crypto AI products in the market can mainly be divided into two forms: 'AI for Crypto' and 'Crypto for AI'.
The former 'AI for Crypto' refers to empowering crypto with AI, mainly focusing on applying AI technology to crypto products to enhance user experience or strengthen the performance of various products by integrating AI elements. For example, using AI for code optimization and security auditing: AI technology can automatically detect and analyze the code of Web3 projects, identifying potential security vulnerabilities and errors, thereby improving the security and stability of projects; participating in on-chain yield strategies: leveraging AI algorithms to analyze market trends and user behavior, formulating more efficient on-chain yield strategies to help crypto users achieve higher returns; integrating AI chatbots to answer user inquiries and improve user experience; using AI Agents to eliminate obstacles in the on-chain user experience, such as automated trading and asset management, enabling users to participate in the crypto market more conveniently.
'Crypto for AI' focuses on leveraging encryption technology to empower the AI industry, utilizing the unique advantages of blockchain technology to address or improve certain aspects of the AI industry. For example, the privacy and transparency of blockchain technology can solve privacy and security issues in the data collection, processing, and storage processes of AI models; by using tokenized model assets, the community can own or use AI models in a decentralized manner; and through blockchain token technology, scattered computing resources can be aggregated to form a computing power market, reducing the cost of training AI models and improving the utilization efficiency of computing resources.
In summary, the essence of Web3 technology lies in its decentralized blockchain infrastructure, which relies on the operation of a token economic system, the autonomous execution of smart contracts, and the powerful efficiency of distributed technology. This not only ensures the precise definition of data ownership but also significantly enhances the transparency and efficiency of business models through the incentive model of tokens. This characteristic acts as a remedy for the common issues of data opacity and vague business models in the AI industry, providing effective solutions. This aligns perfectly with the macro concept that 'AI aims to enhance production efficiency, while Web3 focuses on optimizing production relationships.'
As a result, industry insiders have generally reached a consensus: 'Crypto for AI' shows broader prospects and potential compared to 'AI for Crypto' in terms of market application. This trend has also prompted more and more insiders in the AI industry to actively seek to leverage encryption technology to overcome various challenges and issues faced by the AI industry.
Building a crypto AI ecosystem around the three essential elements of 'data, computing power, and algorithms'
Based on the three core elements of the development of AI large models—'data, computing power, and algorithms'—we can further subdivide them into data, computing, and algorithm model products that cover infrastructure and applications. Among them, data is the foundation for training and optimizing AI models; algorithms refer to the mathematical models and program logic that drive AI systems; computing power refers to the computational resources needed to execute these algorithms, and these three elements are also necessary conditions for the continuous updating and iteration of the models.
The specific product forms within the crypto AI product ecosystem include the following aspects:
At the data level, crypto AI data projects cover data collection, storage, and processing. First, in terms of data acquisition, to ensure the richness and diversity of data, some crypto AI projects use token economic mechanisms to incentivize users to share their private or proprietary data; for example, the Grass project encourages data providers through a reward mechanism, Sahara AI tokenizes AI data assets and launched a dedicated data market, and Vana provides specialized or customized datasets for AI applications through data pools, etc.; in terms of data processing, decentralized data labeling platforms contribute high-quality training datasets for developers, improving the reinforcement learning and fine-tuning mechanisms of AI models, such as Fraction AI (which completed a $6 million financing on December 18), Alaya AI, and Public AI, which provide developers with high-quality training datasets, optimizing the reinforcement learning and fine-tuning processes of AI models. As for data storage, solutions like Filecoin and Arweave ensure the security and permanence of data.
At the computing power level, the training and inference execution of AI models cannot proceed without strong GPU computational resources. As the complexity of AI models increases, the demand for GPU computational resources is also continuously rising. In the face of challenges such as the high demand for high-quality GPU resources, rising costs, and extended waiting times, decentralized GPU computing networks have emerged. These networks create open markets and GPU aggregation platforms, allowing anyone (such as Bitcoin miners) to contribute their idle GPU computing power to execute AI tasks and earn rewards through tokens. Representative projects include Akash, Render, Gensyn, io.net, and Hyperbolic. Additionally, projects like Exabits and GAIB have tokenized physical GPUs, transforming them into financial digital assets on-chain, further promoting the decentralization and liquidity of computing power.
At the algorithm model level, the decentralized AI algorithm networks available in the market are essentially decentralized AI algorithm service markets that connect numerous AI models with different expertise and knowledge. When users pose questions, this market can intelligently select the most suitable AI model to provide answers. Representative products include Bittensor, which aggregates various AI models in a subnet to deliver high-quality content to users; while Pond evaluates the best decentralized models through competition points and incentivizes every model contributor by tokenizing AI models, thus promoting innovation and optimization in AI algorithms.
From this perspective, the current crypto market has built a thriving crypto AI ecosystem around the three pillars of 'data, computing power, and algorithms'.
What are the favorable factors for the crypto AI track in 2025?
However, since the AI Agent Meme market became popular in October, products related to AI Agents have become the new favorites in the crypto AI market, such as the Talus Network project, which announced the completion of $6 million in financing with $150 million in November, specifically creating frameworks and infrastructure for AI Agents.
Additionally, the wave of AI Agent Meme not only ignited a new speculative hotspot in the crypto AI track but also shifted the market's focus from the foundational infrastructure areas of decentralized data, GPUs, etc., to the enthusiastic pursuit of AI Agent applications; for instance, ai16z's market value has exceeded $1 billion, and this trend continues to heat up.
In recent trend outlooks for the crypto industry in 2025 released by multiple institutions, a16z, VanEck, Bitwise, Hashed, Blockworks, Messari, Framework, and others have expressed optimism about the development of the crypto and AI markets, particularly pointing out that products related to AI Agents will see explosive growth in 2025.
At the same time, the heat in the external AI field continues to rise. On December 23, Elon Musk's AI company xAI announced the completion of a new financing round of $6 billion, directly boosting its valuation to $40 billion, further promoting the prosperity of the AI market.
In terms of narrative, OpenAI is undergoing a transformation from GPT to general artificial intelligence AI Agents. It is reported that OpenAI plans to launch a new AI Agent product called 'Operator' in January 2025, which will be able to automatically execute complex operations such as writing code, booking travel, and online shopping. It is expected to ignite the AI market once again, similar to the Sora project at the beginning of 2024. Moreover, Nvidia's annual AI summit will also be held in March 2025, once again becoming the focus of attention in the crypto and AI industries.
Each upgrade of large models by Web2 companies in the AI field, such as Nvidia and OpenAI, ignites hotspots in the AI track, attracting new funding and further igniting the crypto AI track.
At the policy level, newly elected U.S. President Trump has announced the appointment of former PayPal executive David O. Sacks as the White House's head of artificial intelligence and cryptocurrency affairs, responsible for guiding the government in formulating policies in the fields of artificial intelligence and cryptocurrency. This individual has dual investment experience in both the crypto and AI industries, having previously invested in several crypto and AI companies such as Multicoin, and is naturally expected to influence the policies formulated for the integration of crypto and AI.
