AI tokens have become one of the main trends of 2024-2025. Artificial intelligence is developing at a record pace, and more and more projects want to connect it with blockchain. According to CoinMarketCap, this segment grew by 160% in 2024, and CoinGecko notes that 44% of surveyed experts view the sector's prospects positively in 2025.
The best AI tokens of 2025
Each of them has a specific role in its ecosystem and pertains to a particular direction of technology development.
Bittensor (TAO)
Bittensor is a decentralized open-source protocol that combines machine learning and blockchain. It allows neural networks to work together and receive rewards in TAO tokens.
$TAO is also used to access network capabilities and manage its operations. In the long term, the project aims to create an open market for AI-based solutions and products, where developers and users will interact directly.
Internet Computer (ICP)
Internet Computer is a blockchain created by the Dfinity Foundation, which offers an alternative to traditional internet and cloud platforms. The project aims to create conditions for launching Web3 services that are independent of centralized servers. Smart contracts $ICP operate at high speed, do not require gas fees from users, and can interact with other networks.
Internet Computer is developing the artificial intelligence direction, offering new opportunities for hosting and launching AI models based on smart contracts. Developers have access to a full technological stack — with data storage, large-scale processing, and support for Web2 solutions.
NEAR Protocol (NEAR)
NEAR Protocol is positioned as a blockchain for artificial intelligence. It is a high-performance platform tailored for working with AI and next-generation decentralized applications. $NEAR offers infrastructure where AI agents can carry out transactions, perform tasks, and interact with Web2 and Web3 services.
Additionally, thanks to the implementation of Chain Abstraction, NEAR allows algorithms and users to interact with different blockchains through a single account.
Fetch.ai (FET)
Fetch.ai is part of the Artificial Superintelligence Alliance along with SingularityNET and Ocean Protocol. The goal of the alliance is to develop decentralized AI and create an open infrastructure for AGI.
Fetch.ai uses an agent model in which AI-based 'digital twins' automate DeFi processes — from position management to interaction with oracles.
The network is built on Cosmos SDK and supports CosmWasm — a smart contract language that allows complex cryptography and machine learning to be run on the blockchain.
Render (RENDER)
Render Network is a platform for distributed GPU computing. It connects owners of graphics cards who rent out their power with developers and artists who need resources for complex computations and rendering. This allows resource-intensive tasks to be executed faster and cheaper than using one's own equipment.
The project focuses on accessibility and scalability, and its peer-to-peer architecture allows for efficient task distribution and resource savings. Render is used to support generative AI solutions and train language models.
Virtuals Protocol (VIRTUAL)
Virtuals Protocol allows the creation of AI agents that can be tokenized and integrated into user applications. Agent tokens are available on Base networks and #solana and provide ownership, governance, and a share of the income.
The project developed its own Initial Agent Offering (IAO) model for launching agents, as well as the GAME framework that allows them to make autonomous decisions.
One example of using Virtuals Protocol is Ai-dol. These are virtual influencers (vtubers) that run social media, conduct streams, and communicate with users in chats. Thanks to built-in monetization, they generate real profit.
Story (IP)
Story is a blockchain optimized for the tokenization of intellectual property (IP). The project offers an infrastructure through which authors, companies, and even AI algorithms can convert their works into NFTs, license them, and earn without intermediaries — the management of licenses, royalties, and rights is done through smart contracts.
Additionally, Story develops a separate direction — IPFi, which considers intellectual property rights as a digital asset. The Agent TCP/IP framework allows AI agents to automatically obtain licenses, make deals, and distribute income.
The Graph (GRT)
The Graph is a protocol for indexing blockchain data. It simplifies access to information through GraphQL, allowing developers to quickly connect to public information and build decentralized applications without their own servers.
One of the key features of the protocol is subgraphs — schemas by which data is structured for third-party products. Indexers and curators are responsible for maintaining the network. The former process requests and earn rewards in GRT, while the latter highlight useful subgraphs and earn from it.
However, The Graph is not limited to data indexing, offering solutions for AI. For instance, the Semiotic Labs team launched Inference and Agent services that allow AI models to be run directly on the network, using the power of indexers.
DeXe (DEXE)
DeXe offers infrastructure for launching and managing DAOs that does not require programming skills. The project developed a library of over 60 smart contracts and an interface through which voting can be conducted, tokens issued, fundraising carried out, and various governance models set up.
The team is developing the direction of AI agents that participate in votes on behalf of the community and integrates DeXe with third-party platforms like GraFun.
Beldex (BDX)
Beldex is a privacy-focused blockchain that supports both open and private transactions.
The project builds infrastructure for AI that preserves privacy — algorithms can process information without revealing its content. This is important when dealing with sensitive data, for example, in finance or medicine.
Criteria for selecting AI projects for investment
When evaluating AI tokens, it is important to consider not only the theme and direction but also the fundamental characteristics. Below are key criteria that will help determine the prospects and stability of such projects.
Technological innovativeness
It is important that the project offers not just an AI token but genuinely improves technologies: developing new approaches to training, working with data, infrastructure for AI agents, or integration with Web3.
The more useful and innovative the development is, the higher the chances of creating a sustainable and sought-after product.
Market capitalization and liquidity
Low capitalization, in theory, indicates that the project is undervalued. This is associated with high risks, for example, if the development is in its early stages, but also provides greater growth potential. High capitalization, on the other hand, may indicate maturity and reduced volatility of the asset.
It is also important to consider liquidity — high daily trading volumes and the availability of the token on major exchanges allow for easy buying or selling of the asset without significant impact on price. If the project is traded only on obscure platforms with low activity, the level of risk and potential slippage is higher.
However, these factors should be considered only in conjunction with other data to avoid distortions in the form of artificial trading volumes and price manipulations.
Partnerships and support
If the project is backed by major investors, funds, or well-known developers, it adds credibility. Especially if it is not just about investments but about technical partnerships or infrastructure integration.
The role of the token in the ecosystem
The success of the asset directly depends on its role in the project’s tokenomics and sources of organic demand. For example, the token may provide access to AI products, grant governance rights, or revenue distribution. It may also be required for deploying and supporting agents.
If the asset is not somehow related to the main product or service of the project, it raises doubts about its long-term value.
Risks and prospects of investing in AI tokens
AI tokens remain a high-risk and unpredictable segment of the crypto market. The key risks for investors are:
speculative interest — demand for the token may form for short-term profit rather than its utility;
inflated expectations — many projects promise more than they can deliver;
high volatility — prices can fluctuate sharply, even without objective reasons, increasing potential losses.
Coinbase analysts note that a significant portion of AI tokens is overvalued and relies more on expectations than on actual application. Moreover, many projects declare decentralization but depend on centralized AI services and external data sources.
All this makes AI tokens a segment with high growth potential but equally high risks. It is important not to focus on hype but to soberly assess the technological foundation, the role of the token, and the overall maturity of the project.
