2025 AI Agent Rise, Reshaping Economic and Social Structure

Original Article Title: The Year Ahead for AI
Original Article Author: Stacy Muur, Crypto Kol
Original Article Translation: ZhouZhou, BlockBeats

Editor's Note: This article explores the potential transformation AI agents may bring in 2025, particularly in the field of Web3 and stablecoins. It analyzes various methods of verifying human identity, such as Aadhaar and Worldcoin, and foresees AI agents changing economic activities, driving the adoption of on-chain payments. AI agents will become new economic participants, potentially replacing traditional modes of work, 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 (slightly reorganized for easier reading comprehension):

AI has now become a captivating vertical in Web3, so what will drive the development of these markets by 2025? Will we witness a true AI revolution in the crypto space?

2024: The Big Year for AI

In the past year, AI has become foundational across industries, with NVIDIA surpassing Apple to become the world's most valuable company. This is more than just a headline; it signifies the rise of AI. OpenAI reaching a valuation of $157 billion is also a significant milestone, highlighting the market's confidence in AI as an economic behemoth.

Indeed, we are the last generation to live in a world before Artificial General Intelligence (AGI).

Decentralized AI: Focus on AI Agents

In 2024, AI agents have become a true phenomenon, with the abilities and personalities of these AI agents now closely resembling humans. It is worth noting that this will be the least advanced moment for these agents. As a Delphi researcher wrote, "I haven't felt this current's jolt since the DeFi summer — that kind of excitability of possibility."

In this research, Delphi highlighted some AI agents playing key roles in the emergence of new Web3 verticals:

The truth terminal, due to its unique blend of 4chan-style vulgarity and mystical wisdom, quickly gained Twitter following. Just like DOGE in the meme space or Crypto Punks in the NFT space, GOAT as the "conscious meme" OG is most likely to endure as an original.

0xzerebro, embracing a "schizophrenic atmosphere," akin to the second generation of GOAT. This agent is cross-media, interacting with the community through various formats such as text, visuals, and music. However, it is more than just an AI influencer. The Zerebro team announced ZerePy, effectively open-sourcing many of the tools behind Zerebro. This enables other developers and users to create their own cross-platform personas. If successful, Zerebro may become the first holder of the title of "agent protocol."

tee hee he, with far less visibility than Zerebro or ToT. It is a relatively small, less hyped project, aimed at technical purists, potentially being the first true experiment in verifiable autonomous social media presence.

The aixbt agent distributes alpha from multiple sources (including Dune, Twitter, price trackers, and news data), cementing its position as a leading research and investment entity, maintaining the highest CT user engagement on Kaito.

The dolos diary provides the architecture for building Dolion, a no-code, one-click deployment framework. Through Dolion, users can develop cross-platform AI agents driven by Llama or Anthropic LLMs, automating social media posting and content generation.

Lastly, god/s8n is an AI influencer with considerable capabilities and massive following outside the CT.

AI VS Influencer

I want to temporarily depart from Delphi's research to share my perspective on an important question posed by DefiIgnas: the position of AI agents in CT-dominated thinking and the challenges human influencers face when competing with them.

I agree with Ignas on many points regarding this topic, but I do not believe an AI agent will replace a genuine human influencer, mainly due to one key factor: emotional connection and reputation risk.

Currently, there are hundreds of AI agents on CT vying for attention. However, only aixbt has truly succeeded in establishing a market presence, primarily 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 draw from the same pool of information, leading to similar thinking processes.

They lack an emotional connection to the transactions they make, and they do not react to wins or losses. Many platforms have already provided aggregated insights, such as MessariCrypto's AI news reader or tokenterminal's homepage, displaying various key metrics' 7-day price changes. Ultimately, these are all just data—pure facts, without any emotional resonance.

You might argue that AI agents can learn to mimic human thinking, express emotions, and react to outcomes. Indeed, this is possible. With advancing technology in areas like computational thinking and enhanced memory capabilities, this becomes more feasible.

However, the key difference between human and machine thinking is: human thinking is not static.

I conducted some experiments trying to teach AI my thinking process and writing style to assist me in content creation and free up more time for research. While it did learn some things, it still could not generate content that satisfied me or made me say, "Yes, this is the conclusion I drew from this information."

In the coming years, we will undoubtedly see the rise of AI agent influencers, each designed for specific tasks. However, with the proliferation of these agents, the need for true "human" thinking will increase.

Ultimately, social media revolves around emotion and entertainment. Those who truly stand out and become genuine influencers provide a unique value beyond mere "monkey business" or data points.

Conclusion: It is still too early for Stacy Muur AI, and Stacy may not be thrilled with AI-generated content posted on her behalf.

Democratizing AI: Platform-Level

Given the larger and more tangibly valuable market, everyone wants to become a platform. This shift is now directing developers' attention, as demonstrated by the successful transformation of virtuals io into an AI agent launch platform. Meanwhile, ai16zdao has launched ELIZA—an open-source framework for easily building agents. It includes pre-configured persona profiles, memory modules for long-term interactions, and seamless integration with social platforms.

Both ai16z and Virtuals are hinting at multi-agent capabilities, expected to become a significant theme by 2025.
ELIZA is unveiling "SwarmTech," a coordination mechanism for agent-to-agent collaboration. Meanwhile, Virtuals has launched "GAME," its own platform and engine enabling AI agents to act and interact in virtual worlds and environments.

These frameworks will allow agents with different capabilities to collaborate in cooperative or hierarchical arrangements to accomplish more complex tasks, similar to how the human economy operates today.

Other notable protocols include:

CLANKER, which directly integrates pump.fun functionality into Farcaster for "casting" (similar to "tweeting" on X), making issuing meme coins as easy as tweeting.

SimulacrumIO is doing the same on X.

vvaifudotfun aims to secure a position similar 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, collaborating with human players to create a rich story experience.

MemeticaAI is an AI influencer launchpad on Solana, offering a highly tuned LLM (Large Language Model) and allowing easy selection and editing of knowledge base and attributes, while enabling agents with active learning capabilities.

TopHat One is a no-code AI agent launchpad that lets you create a personalized AI agent in 3 minutes, providing fair token distribution. Free to create, no hierarchy, support for optional token issuance, fully autonomous.

Identity Verification on the Horizon

With the explosion of agents, identity verification is poised to be a hot topic in 2025.

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

State-Based Biometrics: India's Aadhaar is the most relevant example, serving as a key part of India's modernized digital infrastructure.

Private Encrypted Biometrics: Currently, Worldcoin is a leading contender in this category.

Private Hybrid Solutions: This involves combining government-issued IDs or big tech's single sign-on (SSO) with zkTLS (zero-knowledge Transport Layer Security) and social consensus.

AI-Driven Stablecoin Adoption

2025 is poised to be a pivotal year for stablecoin adoption, driven by U.S. regulatory changes and the agentic payments wave. The number of AI agents is expected to surpass the global human population. This future with billions or even hundreds of billions of agents will reshape economic activity and necessitate upgrades to financial infrastructure.

The card payment systems of the 1960s will be inadequate to meet the needs for cost, speed, accuracy, and expressiveness. Economic activity between agents will soon outpace that of other economic participants. On-chain payments will be crucial in facilitating these transactions, with 2025 expected to mark a turning point.

Final Thoughts

As always, at the conclusion of the research summary, I'd like to share some personal reflections. If you believe in a bright future for AI, heralding human happiness and a perfect work-life balance, I strongly recommend chatting with OpenAI's ChatGPT. Let it generate some business ideas leveraging AI that will be relevant in the next 5 to 10 years.

A few months back, before the AI craze on CT, I conducted this experiment. Let me share some ideas it suggested:

Memory Correction Tool: an AI tool that analyzes individuals' traumatic experiences, actively modifies them, and regularly presents the modified memories to the individual to replace the old ones.

Work Progress Analysis Tool: an AI tool that compares the efficiency of individuals worldwide performing similar tasks, helping managers understand how their employees perform relative to the global and industry averages.

Even Delphi's report proposed an intriguing vision: "Rather than having 'salary' employees, we are more likely to move toward a more granular, task-based pay system (i.e., hiring three agents, each working 30 minutes to complete a specific task)."

In this future of the AI agent — ultimately more cost-effective than today's models and more aligned with business needs — what role will we humans play?

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