Overview

With the rapid advancement of artificial intelligence (AI) and its integration with blockchain technology, AI tokens have emerged as a thriving sector in the cryptocurrency industry. These tokens bridge cutting-edge AI developments and decentralized finance, gradually becoming a popular investment choice. From the early days of AI-focused infrastructure tokens to the latest wave of AI Agent tokens, the evolution of this market reflects the constant interplay between technological progress and shifting investor interest.

In 2024, AI Agent tokens, such as Virtuals Protocol, have become market favorites, attracting substantial investor attention due to their novel applications and compelling narratives. Meanwhile, older AI tokens like WLD (Worldcoin) and ARKM (Arkham) have struggled to maintain relevance, failing to keep up with the rapid pace of innovation and changing market dynamics.

Source: https://www.statista.com/outlook/tmo/artificial-intelligence/worldwide#market-size

Development History

The emergence of AI tokens can be traced back to around 2017. At that time, with the rise of blockchain technology, multiple projects began exploring integrating it with artificial intelligence (AI). Most of these projects focused on providing decentralized infrastructure for AI, such as data sharing, computing resource allocation, and decentralized machine learning algorithms. For example, tokens like RENDER (a decentralized GPU solution provider) represented the infrastructure-type AI tokens of this period, aiming to leverage blockchain technology to address issues related to data privacy and computing resource distribution in the AI ecosystem.

Although these projects initially attracted some market attention, their market performance did not meet expectations due to the early-stage nature of the technology and low industry recognition. After the industry bubble burst, many early AI tokens gradually faded from the market, even leading to trust crises.

However, the concept of AI tokens did not emerge out of nowhere; it originated from early explorations of integrating blockchain and AI technology. Between 2017 and 2019, as the crypto boom surged, multiple projects attempted to utilize blockchain’s decentralized nature to support AI. For instance, SingularityNET (token: AGIX) was one of the first projects to combine AI services with blockchain. It aimed to create a decentralized AI marketplace, allowing developers to share and trade AI models. During this period, AI tokens primarily focused on infrastructure development, attempting to solve challenges such as the high cost of computing resources and data privacy in AI applications.

As the crypto market matured between 2021 and 2023, more well-known AI tokens, such as Worldcoin (WLD) and Arkham (ARKM), emerged. WLD proposed an ambitious vision of distributing universal basic income (UBI) through iris scanning, while ARKM specialized in using AI technology to analyze crypto transaction data and identify behavioral patterns. Despite being backed by strong technical teams and investment support, these projects eventually encountered bottlenecks, and their market performance failed to sustain long-term growth.

The Rise of AI Agent Tokens

The year 2024 marked a turning point in the rise of AI Agent tokens. AI Agents are intelligent entities capable of independently executing tasks, self-learning, and interacting with humans or other systems. Unlike traditional AI projects, AI Agent tokens rely on technological innovation and emphasize stronger community engagement and cultural narratives, making them the focal point of the market. Emerging tokens like VIRTUAL have become prominent examples of this trend.

One notable example is a decentralized AI investment fund (DAO) on Solana, which leverages AI-powered agents to analyze market trends and execute trades. This project was inspired by prominent venture capitalist Marc Andreessen and introduced an open-source framework called Eliza, allowing developers to efficiently build AI Agents. Meanwhile, Virtuals Protocol (token: VIRTUAL) has developed an AI Agent issuance platform on the Base blockchain, enabling users to create and trade AI-powered tokens.

The rise of these new AI tokens coincided with the surge of the AI Agent boom in Q4 2024, with market enthusiasm for this sector continuing into 2025. According to data, as of January 2025, the total market capitalization of AI Agent tokens had exceeded $16.9 billion. By February 27, 2025, the market cap stood at approximately $5.335 billion.

Source: https://coinmarketcap.com/view/ai-agents

Why is the Market Favoring AI Agent Tokens?

1. Advancements in AI and Expanding Use Cases

AI technology has seen rapid progress in recent years, particularly in natural language processing, computer vision, and automated decision-making. This has driven a surge in demand for AI Agents, which are more versatile than traditional AI infrastructure projects and can address real-world industry challenges.

For example, AI Agents are already replacing human labor in customer service, automated trading, and personalized advertising, offering faster and more efficient solutions. As these applications expand, AI Agent tokens have gained significant market traction.

Source: https://www.statista.com/outlook/tmo/artificial-intelligence/worldwide

2. Combining Decentralization with Smart Contracts

Blockchain technology is inherently decentralized, and AI Agent projects leverage this advantage to the fullest. The decentralization of AI Agents means they are no longer controlled by a single institution or company but operate in a decentralized manner, ensuring data transparency and security.

Additionally, the integration of smart contracts enables AI Agent tokens to facilitate automated transactions and task execution, greatly enhancing efficiency and credibility.

3. Growing Market Demand

Over the past few years, investors have been highly optimistic about combining blockchain and AI, particularly in the rapidly evolving Web3 ecosystem. AI Agent tokens align with this trend and cater to users’ increasing demand for personalized services.

From AI applications in enterprises to broader intelligent services, AI Agents provide greater market demand and potential, attracting significant investor interest.

4. Optimized Tokenomics Models

Compared to early AI infrastructure tokens, AI Agent tokens have introduced more optimized incentive mechanisms and tokenomics designs.

For example, many AI Agent projects offer attractive rewards to developers, users, and the community. Users can earn additional token incentives by participating, contributing, or developing AI Agents. This mechanism fosters the project’s sustainable growth and enhances user engagement and loyalty.

5. Broader Appeal and Lower Entry Barriers

AI Agent tokens often revolve around grand narratives such as “autonomous economy” and “decentralized intelligence.” For example, the concept of an “AI-driven investment DAO” appeals not only to tech enthusiasts but also to investors seeking automated income generation.

Virtuals Protocol has adopted a Pump.fun-style token issuance model, allowing ordinary users to easily create and trade AI Agent tokens, lowering participation barriers. In contrast, older AI tokens like WLD and ARKM focus on more vertical narratives (identity verification, data analysis) and lack sufficient community engagement and imaginative appeal.

6. Meme Culture and Community-Driven Growth

AI Agent tokens have successfully integrated into the crypto market’s Meme culture. The launch of Degen Spartan AI gained massive traction due to its sharp and humorous social media presence, with some even suspecting it was secretly controlled by a human. This personalized interaction significantly boosted the project’s discussion and visibility.

Virtual’s Luna, a virtual K-pop idol, engages with audiences 24/7 on TikTok and X (Twitter), strengthening its connection with younger users. In contrast, older tokens like FET and WLD follow a more traditional VC coin model, maintaining a distant relationship with their communities and lacking Meme-driven appeal.

7. Technological Innovation and Ecosystem Expansion

AI Agent tokens are not just conceptual; they actively drive ecosystem development through technical frameworks. The Eliza framework has become a popular tool for developers to create AI agents, maintaining high engagement on GitHub. Meanwhile, Virtual’s GAME framework empowers AI agents with autonomous operations, focusing on integration with gaming and social applications.

These open-source tools have attracted many developers, forming a positive feedback loop. In contrast, older AI tokens have seen slower technological advancements. For instance, while FET has planned token burns to create deflationary pressure, its ecosystem progress has struggled to keep up with the market’s rapid evolution.

8. Profit Expectations and Speculative Interest

AI Agent tokens are closely linked to high-return expectations. Virtual drives market demand through its value capture model, where transactions require spending $VIRTUAL, creating economic incentives. At the same time, governance and revenue-sharing mechanisms offer additional rewards for holders, increasing investor appeal with the prospect of short-term profits. On the other hand, established AI tokens tend to focus more on practical applications. Still, their conservative economic models make them less attractive to a market constantly seeking high-growth potential.

Key AI Token Projects

Established AI Tokens

1. Worldcoin (WLD)

Introduction:

Worldcoin (WLD) is a project that aims to verify identity through iris scanning and distribute Universal Basic Income (UBI). Its goal is to create a global identity authentication and fair wealth distribution system. The WLD token is designed as both an identity verification tool and a governance token, helping people establish digital identities and facilitating fair wealth distribution worldwide.

Development History:

Since its launch, Worldcoin has garnered widespread attention, especially for its innovative approach to iris scan-based identity authentication. However, concerns over privacy issues and technical feasibility have hindered its market growth. The price of WLD has declined by more than 50% from its all-time high, and the project is under increasing regulatory scrutiny, preventing it from fully realizing its grand vision.

Source: https://world.org/

2. Arkham (ARKM)

Introduction:

Arkham (ARKM) focuses on crypto data analytics, utilizing AI technology to analyze on-chain data and detect trading patterns. The project aims to provide users with valuable insights into crypto market behaviors, particularly in fund movement tracking and market trend prediction.

Development History:

Arkham initially gained market attention due to its innovations in on-chain data analysis. However, as the understanding of AI applications in crypto deepened, Arkham’s technical progress and market performance have stagnated, and its market capitalization has struggled to grow, limiting its application scope.

Source: https://arkm.com/

Emerging AI Tokens

1. ai16z

Introduction:
ai16z is a decentralized AI investment fund (DAO) built on the Solana blockchain. It utilizes AI agents to analyze market trends and execute automated trading decisions. Its open-source framework, Eliza, enables developers to build and deploy AI agents quickly. Beyond being an investment tool, ai16z also aims to create a decentralized AI Agent ecosystem that enhances machine learning and decision-making capabilities.

Development History:
Since its launch in October 2024, ai16z’s market cap has rapidly surged, reaching nearly $2.5 billion in early 2025, making it the first AI token on Solana to surpass this milestone. Driven by technological innovation, decentralized governance, and strong market demand, it has emerged as a leader in the AI Agent token space.

Key Innovations:

• Decentralized AI Investment Fund
• Market trend analysis via AI Agents
• Open-source framework supporting AI Agent development

Source: https://coinmarketcap.com/currencies//

2. Virtuals Protocol (VIRTUAL)

Introduction:
Virtuals Protocol (VIRTUAL) is an AI Agent issuance platform built on the Base blockchain, allowing users to create, trade, and deploy AI agent tokens. By combining blockchain and AI, Virtuals gives AI agents the ability to learn and make decisions autonomously. Users can create and interact with AI Agents on the platform in a decentralized environment.

Development History:
Since its launch, Virtuals has gained significant attention from investors and developers, particularly for its vision of building virtual worlds through AI agents. By early 2025, VIRTUAL’s market cap exceeded $4.5 billion, making it one of the top 40 cryptocurrencies by market capitalization.

Key Innovations:

• Users can create and trade AI Agent tokens
• Deep integration of AI with virtual world interactions
• AI Agents equipped with autonomous behavior and decision-making capabilities

Source: https://app.virtuals.io/?sortBy=totalValueLocked&sortOrder=desc&page=1

3. SingularityNET (AGIX)

Introduction:
SingularityNET is one of the first projects to integrate AI and blockchain, with its token AGIX representing a decentralized AI service marketplace. The platform allows developers to share and trade AI models, making AI technology more accessible and open. SingularityNET aims to break down barriers in AI development and promote decentralization in the AI industry.

Development History:
Launched in 2017, SingularityNET conducted its ICO in 2018. Despite market fluctuations, the project has continued to strengthen its influence in AI and blockchain. SingularityNET has gradually established itself as a major player in decentralized AI development by partnering with various key organizations and technical teams.

Key Innovations:

• Decentralized AI service marketplace
• AI model trading and sharing
• Open-source framework to support AI developers

Source: https://singularitynet.io/

AI tokens have evolved alongside technological advancements and shifting market demands. Early AI tokens like Worldcoin and Arkham focused on infrastructure and data privacy, but failed to achieve long-term breakthroughs due to technical challenges and limited market awareness.

In contrast, as AI technology has matured, AI Agent tokens like Virtuals Protocol have gained mass adoption by offering practical applications and decentralized innovations. These emerging AI tokens are set to drive deeper integration between blockchain and AI, opening up new frontiers in decentralized intelligence.

Comparing Established vs. Emerging AI Tokens

Established AI tokens, such as FET, WLD, and ARKM, primarily focus on AI infrastructure, addressing issues related to data privacy and computing resources. These tokens initially gained a first-mover advantage during the early stages of AI and blockchain integration. However, as the market shifts toward AI Agents, these tokens gradually lose their innovation momentum, leading to weaker market performance.

In contrast, emerging AI tokens such as VIRTUAL and Swarms align with the AI Agent trend, emphasizing intelligent agent applications like automated trading and collaborative networks. Benefiting from the 2024 AI Agent market boom, these tokens have shown strong short-term performance.

Overall, established AI tokens need to overcome technological or narrative bottlenecks to regain market attention, while emerging AI tokens are rapidly gaining traction due to their novelty and market speculation. However, their long-term value remains to be seen. As AI Agent technology advances, new AI tokens are expected to become the new driving force of the crypto market.

Future Trends

1. The Continued Rise of AI Agent Narratives

Trend: AI Agents (intelligent agents) are set to become the core driving force behind AI tokens. At the beginning of 2025, major tech events such as CES brought AI Agents into the spotlight. These AI systems, capable of autonomously executing complex tasks (such as automated trading, data analysis, and collaborative networks), attract significant capital and developer interest.

Impact: AI Agent-related tokens (such as TAO, Bittensor, or emerging tokens like Swarms) may experience significant growth in the next 1-2 years. The market’s anticipation for “decentralized AI agents” is reminiscent of the DeFi boom in 2020, indicating huge narrative potential.

Prediction: In the short term (2025), AI Agent tokens may experience rapid price surges due to speculation, but their long-term value will depend on real-world applications, such as large-scale deployments in finance, healthcare, or supply chain industries.

2. The Demand for Computing Power Driving the Rise of Resource-Based Tokens

Trend: The increasing demand for computing power (GPU, storage) to train and operate AI models is fueling the growth of the decentralized computing market. Projects such as Render (RNDR) and Filecoin are filling this gap.

Impact: As AI models grow in complexity (e.g., multimodal AI models), tokens that provide distributed computing power or storage will gain more attention. This trend may give rise to a new category of “computing economy” tokens.

Prediction: By 2026, computing-focused AI tokens may become a dominant sector in the market, particularly as cloud computing costs continue to rise.

3. Industry Consolidation and Strategic Alliances

Trend: Established AI tokens (such as FET, AGIX, and OCEAN) are seeking synergies through mergers (e.g., the Artificial Superintelligence Alliance, ASI), while new projects are forming deeper integrations with major blockchains like Ethereum, Solana, and Base.

Impact: This consolidation may lead to market centralization, where leading projects gain more resources while smaller projects must find unique differentiators to survive.

Prediction: Over the next 2-3 years, the AI token market may evolve into a few “super ecosystems”, similar to how Uniswap and Aave dominate DeFi, attracting most capital and developers.

4. The Expansion of Cross-Chain and Multimodal Applications

Trend: AI tokens will no longer be confined to a single blockchain (e.g., Ethereum), but will expand to high-performance chains such as Solana and Base. At the same time, projects that support multimodal AI (text, image, audio) will gain a competitive advantage.

Impact: Cross-chain compatibility and multimodal capabilities will become key factors in determining project valuation.

Prediction: By 2027, AI tokens that support multi-chain deployment and diverse applications could dominate the market.

Challenges

As a product of the integration between artificial intelligence and blockchain technology, AI tokens have great potential but face multiple challenges. These challenges impact project development and may determine their survival in the market.

1. High Technical Implementation Difficulty

Challenge: Many AI token projects claim to achieve decentralized AI computing, data sharing, or intelligent agents, but in reality, implementing these technologies is complex and costly. For example, distributed AI model training must solve bandwidth, latency, and data consistency issues.

Impact: If projects fail to deliver the functionalities promised in their whitepapers, users and investors may lose confidence, leading to a decline in valuation.

Case Study: Some early AI token projects failed to achieve large-scale adoption due to technical bottlenecks, gradually becoming marginalized in the market.

2. Market Speculation and Bubble Risks

Challenge: AI tokens are highly influenced by market sentiment, especially when new narratives (such as AI Agents) emerge, leading to short-term surges followed by sharp corrections. Projects lacking strong fundamentals are particularly vulnerable.

Impact: Investors may suffer losses due to high volatility, reducing trust in AI tokens.

Current Situation: In early 2025, some emerging AI tokens (such as Zerebro) experienced rapid price surges, driven by the AI hype, only to drop sharply afterward.

Source: https://coinmarketcap.com/currencies/zerebro/

3. Intense Competition and Lack of Differentiation

Challenge: Competition in the AI token market is increasing, with established projects (such as FET and WLD) and new projects (such as VIRTUAL and Swarms) overlapping in features and narratives, making it hard to establish unique advantages.

Impact: Projects that fail to differentiate themselves may be eliminated, with market resources concentrating on leading projects.

Trend: New projects need to find niche areas (such as privacy AI and computing power leasing) to break through the competition.

4. Regulatory Uncertainty

Challenge: The combination of AI and blockchain involves issues related to data privacy, algorithm transparency, and financial compliance. Global regulatory policies remain unclear. For instance, the EU AI Act or U.S. securities laws may impose strict restrictions on AI tokens.

Impact: Stricter regulations could hinder project operations, with potential fines or shutdown risks.

Prediction: In the coming years, non-compliant projects may be eliminated, and regulatory compliance will become a key competitive factor.

Source: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai

5. Dependence on Computing Power and Infrastructure

Challenge: AI tokens rely on powerful computing resources (such as GPUs) and decentralized networks, yet current blockchain infrastructure (such as Ethereum’s high gas fees and Solana’s stability issues) struggles to meet AI demands fully.

Impact: Infrastructure limitations may hinder project scalability and increase operational costs.

Case Study: Render (RNDR) is positioned as a decentralized computing power solution but still relies on external hardware support.

Source: https://rendernetwork.com/

6. User Adoption and Ecosystem Development

Challenge: AI tokens need to attract developers, businesses, and end-users, but decentralized AI’s real-world applications remain limited, making it hard for the average user to perceive their value.

Impact: Slow ecosystem development may lead to project stagnation and reduced token liquidity.

Current Situation: Established projects like FET have relatively mature ecosystems, but many emerging projects are still in their early stages with insufficient adoption.

7. Data Privacy and Security Concerns

Challenge: AI token projects often involve data sharing or analysis, raising concerns about how to protect user privacy in a decentralized environment and prevent data breaches.

Impact: Security vulnerabilities or privacy-related scandals could destroy a project’s reputation, causing user loss.

Case Study: Worldcoin (WLD) faced intense controversy over iris scanning privacy issues, leading to mixed market reactions.

Source: https://www.reuters.com/markets/currencies/spanish-watchdog-tells-worldcoin-delete-all-iris-scan-data-2024-12-19/

8. Funding and Sustainability Pressure

Challenge: Developing AI technology requires significant funding, but many projects rely on initial coin offerings (ICOs) or venture capital, lacking a long-term profitability model.

Impact: Funding shortages may cause projects to stall, particularly for smaller teams. For example, in 2021, Microsoft invested $1 billion in OpenAI, significantly accelerating the development of GPT-3 and other AI innovations. OpenAI’s R&D costs have reached several billion dollars.

Prediction: Future markets may favor projects with clear business models.

Source: https://boast.ai/blog/ai-in-2024-us-announces-100-million-toward-rd-as-openai-breaks-vc-funding-records/

Conclusion

The evolution of AI tokens reflects technological advancements and demonstrates the market’s strong demand for more efficient and intelligent solutions. From the initial infrastructure-focused tokens to the latest AI Agent-driven innovations, AI tokens have matured and diversified through the deep integration of blockchain and artificial intelligence technologies.

The year 2024 marked a key turning point for the rise of AI Agent tokens. Emerging tokens like Virtuals quickly captured the attention of investors through innovative technology and strong community-driven momentum, opening up new application scenarios at the intersection of blockchain and artificial intelligence.

As technology advances and market demands shift, AI Agent tokens are expected to lead industry trends and drive rapid development in the coming years. For investors, AI Agent tokens are symbols of technological innovation and promising opportunities in emerging markets. This trend will undoubtedly spark more innovations and collaborations for professionals in the blockchain and AI sectors, pushing the entire industry to new heights.

However, the rapid development of AI tokens also faces multiple challenges, including technological maturity, market regulations, community building, and intense competition. While AI technology has made significant progress, ensuring long-term stability and widespread adoption still requires technological optimization and solutions for data privacy and compliance. Additionally, maintaining an active community, enhancing user engagement, and standing out in a highly competitive market will depend on both technological and market leadership.