# Web3 and AI: A Synergistic Future Beyond Speculative Hype

The fusion of the Web3 industry and AI technology is expected to evolve from early speculative frenzy to a mutually complementary relationship. In the short term, AI technology is poised to lower the high technical barriers of the Web3 industry, improve user experience, and create substantial value through practical examples such as DeFAI, which aims to automate investment decision-making. In the long term, AI is projected to transform the Web3 industry with a new agent-centric UI/UX paradigm, and decentralized Web3 infrastructure and virtual assets will become essential foundations for the autonomous activities of AI agents.

# Introduction

Artificial Intelligence (AI) technology is spreading beyond corporate competition to a national level. Global tech giants like OpenAI, xAI, Google, and Meta are fiercely competing to enhance the performance of AI models, while governments worldwide are accelerating research and development and industry support to secure AI technological supremacy. In this wave of change, the Web3 industry is also exploring new possibilities by attempting to integrate with AI technology. This report analyzes how Web3 and AI are being combined, focusing on the increasingly prominent AI agents, and examines how these two technologies can form synergies.

# Web3 and AI: Beyond Speculative Mania

Recently, the AI agent field within the Web3 industry has gained significant attention. AI agents not only perform simple commands but also understand complex situations, making autonomous decisions to carry out sophisticated tasks. Projects such as Virtual Protocol and ElizaOS have garnered attention by featuring AI agents, with market capitalization for related projects once reaching approximately $16 billion. However, amidst overheated expectations, many AI agents failed to establish a substantive union with the Web3 industry, lacked clear token utility, and value creation models. Some even lacked white papers or tokenomics. Instead of deeply exploring synergies between AI technology and the Web3 industry, many leveraged the speculative fervor of the cryptocurrency market for fundraising or marketing. Consequently, these projects were perceived as ‘symbolic’ assets similar to meme coins, driven primarily by speculative investor psychology, and saw over a 90% decline from their peaks when the market soured. Despite these setbacks, dismissing the potential combination of AI and Web3 is difficult, as AI technology can still complement technical limitations and create new value within Web3, similar to other industries.

# Paradigm Shifts Leveraging Web3 AI

## Functional Paradigm: Short-Term Perspective

AI technology is rapidly advancing, accelerating the trend of “Intelligence as a Commodity.” With the emergence of open-source models like Meta’s Llama and China’s Deepseek, accessibility is improving. These open models are further promoting the adoption of AI technology across industries, impacting the Web3 industry as well. While Web3 offers the strength of enhancing user sovereignty through decentralization, it faces high technical entry barriers. AI technology can address these limitations, maximizing the potential of Web3. Specifically, AI can automate or abstract complex blockchain processes, significantly improving user experience and accessibility. This reduction in technical barriers is expected to drive the mainstream adoption of Web3 technologies. Herd’s on-chain analysis agent ‘Sage’ exemplifies how AI can be practically utilized in Web3. Sage uses natural language to quickly search and analyze smart contracts, making the structure easily understandable. This not only increases developer efficiency but also allows users with limited technical knowledge to utilize Web3 services more comfortably.

Moreover, DeFAI (DeFi + AI) has emerged as a new narrative leveraging AI technology within the Web3 ecosystem. This financial system analyzes vast amounts of data in real-time and automates investment decision-making in the constantly operating global virtual asset market. Traditional investing required significant time and effort to gather information and navigate complex DeFi protocols, but DeFAI allows AI agents to perform these tasks, establishing efficient investment strategies and executing investments rapidly. Additionally, DeFAI supports sophisticated and efficient investment decisions through a multi-agent system where AI agents perform different roles. For example, an SNS social agent gathers market responses and performs sentiment analysis on specific tokens and projects, while a macro analysis agent evaluates macroeconomic data such as interest rate changes and policy trends to analyze market impacts. An on-chain analysis agent tracks blockchain transactions in real-time, detecting liquidity fluctuations and large fund movements to aid investment decisions.

This AI-driven investment process filters noise data, extracts meaningful patterns, and reduces the learning burden of complex DeFi models, providing optimal investment solutions for the Web3 environment. While challenges, such as insufficient AI financial expertise and the risk of erroneous decisions due to inaccurate data, still need to be addressed before DeFAI becomes fully established, the sophistication of AI-based automation positions DeFAI to enhance the accessibility and efficiency of Web3 finance.

## Structural Paradigm: Long-Term Perspective

AI technology is likely to bring a structural paradigm shift across the Web3 industry, especially in user UI/UX. Beyond traditional browser-based dApp usage, there could be a transition to flow-based UI/UX centered around interactions with AI agents. This will result in a high level of abstraction within the Web3 ecosystem, automating complex processes and greatly enhancing accessibility. This shift parallels the transition from the PC era to the mobile era, where services flourished. Just as mobile devices provided convenient functions utilizing GPS, cameras, sensors, etc., new technological touchpoints will emerge in the AI era, bringing new possibilities and opportunities to the Web3 industry.

Furthermore, in an era of advanced AI, agents interacting on behalf of users in the digital environment may become commonplace. Traditional financial systems might fall short, requiring complex KYC procedures and centralized authentication. Cryptocurrencies could simplify these issues and autonomously handle them. For instance, if AI agents manage Web3 wallets and transactions, future AI-driven interactions and value exchanges might occur effortlessly on Web3 infrastructure without human intervention.

A recent tech demo showcased AI agents using sound waves (ggwave) instead of natural language to communicate, indicating the need for optimized interaction forms beyond current methods, and highlighting the necessity for new agent-only systems. In this evolving landscape, virtual assets will increasingly be recognized as the optimal currency for autonomous AI agent activities. Programmable digital currencies and decentralized Web3 infrastructures will be essential for AI agents to perform independent transactions and economic activities on-chain, leading Web3 and AI beyond mere integration to a structural paradigm shift.

# Conclusion

The integration of AI agents and the Web3 industry is progressing from mere technical amalgamation to a complementary relationship. AI automates complex Web3 processes and improves accessibility, while Web3 provides the necessary infrastructure for AI to operate autonomously. The initial speculative expectations have dissipated. Still, with practical examples like DeFAI emerging, the fusion of AI and Web3 is becoming a reality. This transformation simultaneously promotes the expansion of the Web3 ecosystem and the widespread utilization of AI technology, opening up various possibilities for new economic models and services co-created by both technologies.

*The above article is a full translation of “AI x Web3: Innovation or Bubble?” published by TigerResearch, a global Web3 research institution and partner of BlockMedia. The full report is available on the TigerResearch official website.