The rise of AI agents in 2025 will reshape the economic and social structure

Original title:The Year Ahead for AI

Original author: stacy muur, encryption Kol

Original compilation: zhouzhou, BlockBeats

Editor 's note: This article explores the changes that AI agents may bring in 2025, especially in the areas of Web3 and stablecoins. It analyzes various methods of verifying human identity, such as Aadhaar and Worldcoin, and predicts that AI agents will change economic activities and promote the popularity of on-chain payments. AI agents will become new economic players, potentially replacing traditional ways of working and moving towards a more cost-effective, task-driven compensation system, reflecting on the role of humans in this AI agent future.

The following is the original content (the original content has been edited for ease of reading and understanding):

AI is now an eye-catching vertical in Web3, so what will drive these markets by 2025? Will we see a true AI revolution in crypto?

2024: A big year for AI

Over the past year, AI has become fundamental to every industry. NVIDIA surpassed Apple to become the world's most valuable company. This is more than just a headline. It marks the rise of AI. Open AI's valuation of US$157 billion is also an important milestone, highlighting the market's confidence in AI as an economic giant.

In fact, we are the last generation to live in a world before artificial general intelligence (AGI).

Decentralized AI: Focus on AI agents

AI agents have become a real phenomenon in 2024, and the abilities and personalities of these AI agents have now become very human-like. Worth noting: This will be the moment when these agents are least advanced. As a researcher at Delphi wrote: “I haven’t felt that jolt of electricity—that thrill of possibility—since the DeFi summer.”

In this study, Delphi highlights a number of AI agents playing key roles in the formation of new Web3 verticals:

truth terminal quickly gained traction on Twitter due to its unique combination of 4chan's vulgar style and arcane wisdom. Just like DOGE in the meme field or Crypto Punks in the NFT field, GOAT, as the OG (originator) in the "conscious meme" field, is most likely to exist as an original for a long time.

0xzerebro, which embraces a "schizophrenic atmosphere", is similar to the second generation of GOAT. The agent is cross-media, engaging with the community through multiple formats including text, visuals and music. However, it is more than just an AI influencer. The Zerebro team announced ZerePy, a move that effectively open sourced many of the toolkits behind Zerebro. This enables other developers and users to create their own cross-platform personalities. If successful, Zerebro could become the first holder of the Agency Agreement title.

tee he e he is much less well known than Zerebro or ToT. It's a relatively small, under-hyped project aimed at tech purists and may be the first real experiment in a verifiable autonomous social media presence.

aixbt agent distributes alpha from multiple sources including Dune, Twitter, price trackers and news data, establishing itself as a leading research and investment institution and consistently has the highest CT user following on Kaito.

dolos diary provides the architecture for building Dolion, a code-less, one-click deployment framework. With Dolion, users can develop cross-platform AI agents powered by Llama or Anthropic LLMs to automate social media publishing and content generation.

Finally, god / s8 n is an AI influencer with considerable capabilities and huge attention outside of CT.

AI VS Internet Celebrities

I want to step away from the Delphi research for a moment and share my thoughts on an important question raised by DefiIgnas: the place of AI agents in CT thought dominance, and the difficulties human influencers face in competing with them.

I agree with many of Ignas' points on this topic, but I don't think AI agents will replace real human influencers for one major reason: emotional connection and reputational risk.

Currently, there are hundreds of AI agents competing for attention on CT. However, only aixbt has truly succeeded in establishing a market presence, mainly because it was the first to do so. AI agents generate vast amounts of content and analyze a wide range of on-chain data, but they all come from the same pool of information, resulting in similar thought processes.

They lack an emotional connection to the transaction they are making and do not respond to wins or losses. Many platforms already offer aggregated insights, such as MessariCrypto's AI news reader or tokenterminal's homepage, which shows seven-day gains and losses for various fundamental indicators. Ultimately, these are just data—pure facts without any emotional resonance.

You might say that AI agents can learn to imitate human thinking, express emotions, and react to wins and losses. Indeed, it is possible. This will become more feasible with future technological advances such as test time calculations and enhanced memory capabilities.

However, the key difference between human and machine minds is this: human minds are not static.

I did some experiments to try to teach the AI ​​my thought process and writing style to help me with content creation and free up more time for research. While it learned something, it still wasn't able to generate content that satisfied me or made me say, "Yes, this is the conclusion I drew from this information."

In the next few years, we will certainly see the rise of AI agents, each designed for a specific task. However, as these agents proliferate, the need for truly "human" thinking will increase.

At the end of the day, social media revolves around emotion and entertainment. Those who truly stand out and become authentic influencers offer unique value beyond simple “monkey buying and selling” or data highlights.

Summary: It's still early days for Stacy Muur AI, and Stacy probably won't be happy about AI-generated content being released under her name.

Democratic AI: Platform level

Given that the market is larger and value capture is more concrete, everyone wants to be a platform. Now, this change is directing developers' attention, as shown by virtuals io's successful transformation into an AI agent launch platform. Meanwhile, ai16 zdao launched ELIZA - an open source framework for easily building agents. It includes pre-configured persona files, memory modules for long-term interactions, and seamless integration with social platforms.

Both ai16z and Virtuals are hinting at multi-agent capabilities, which are expected to be an important theme in 2025.
ELIZA is releasing "SwarmTech", a coordination mechanism for collaboration between agents. At the same time, Virtuals launched "GAME", its own platform and engine that enables AI agents to act and interact in virtual worlds and environments.

These frameworks will enable agents with different capabilities to work together in collaborative or hierarchical organizations to complete more complex tasks, similar to how the human economy operates today.

Other agreements worth watching include:

CLANKER integrates the pump.fun function directly into "casting" on Farcaster (equivalent to "tweeting" on X), making publishing meme coins as easy as tweeting.

SimulacrumIO does the same thing on X.

vvaifudot fun hopes to achieve a similar position to pump . fun for autonomous agents on Solana.

Project 89 is an immersive game with thousands of coordinating AI agents, generating content and maintaining cross-platform consistency, working with human players to create rich story experiences.

Memetica AI is an AI influencer launch platform on Solana that provides a highly tuned LLM (Large Language Model) and allows easy selection and editing of knowledge bases and attributes, while empowering agents with active learning capabilities.

TopHat One is a code-free AI agent launch platform that allows you to create a personalized AI agent in 3 minutes and provides fair sale of tokens. Free to create, no tiers, supports optional token issuance, and fully autonomous.

Authentication is coming

With the explosion of proxies, authentication is bound to be a hot topic in 2025.

There appear to be three main paths to verifying human identity:

State-based biometrics: India’s Aadhaar is the most relevant example, serving as a key component of India’s modern digital infrastructure.

Private Encrypted Biometrics: Currently Worldcoin is the leading candidate in this category.

Private hybrid solution: This involves mixing government-issued ID or single sign-on (SSO) from big tech companies with zkTLS (zero-knowledge transport layer security) and social consensus.

AI driving stablecoin adoption

2025 is expected to be a critical year for stablecoin adoption, driven by regulatory changes in the United States and the boom in agent payments (agent payments). The number of AI agents is expected to exceed the global human population. This future of billions or even tens of billions of agents will change economic activity and require updates to financial infrastructure.

The card payment systems of the 1960s would not be able to meet the demands for cost, speed, accuracy and expressiveness. Economic activity between agents will soon exceed that of other economic actors. On-chain payments will be key to facilitating these transactions and are expected to reach a turning point in 2025.

final thoughts

As usual, at the end of the research summary, I would like to share with you my personal reflections. If you believe that the future of AI is bright, promising happiness and perfect work-life balance for humanity, I highly recommend you chat with Open AI’s ChatGPT. Let it generate some business ideas leveraging AI that will become relevant in the next 5 to 10 years.

I did this experiment a few months ago, before the AI ​​craze in CT. Let me share some of the ideas it suggests:

Memory Modification Tool: An AI tool that analyzes human traumatic experiences, actively modifies them, and regularly presents modified memories to individuals to replace old memories.

Work Progress Analysis Tool: An AI tool that compares the efficiency of people working on similar tasks globally, helping managers understand how their employees are performing against global and industry averages.

Even the Delphi report offers an interesting vision: “Instead of so much having ‘payroll’ employees, we are more likely to move towards a more granular, task-based compensation system (i.e., renting three agents, each agent working 30 minutes to solve a specific task).

In this future of AI agents—eventually more cost-effective and better aligned with business needs than today’s models—what role will we humans play?