2025 will be the year of AI agents, say Web3 execs
Artificial intelligence agents will transform the Web3 by 2025, with cryptocurrency staking and onchain trading emerging as first uses, industry executives told Cointelegraph.
Agentic AIs – machines that autonomously pursue complex goals – are already shaping the digital economy, building Web3 applications, launching tokens, and autonomously interacting with people.
In the year By 2025, “AI agents are expected to play a more significant role in decentralized societies,” JD Serafin, developer of Web3 AI at Rainmaker, told Cointelegraph.
They also face headwinds, including technical challenges, regulatory hurdles and centralization, Michael Casey, founder of the Decentralized AI Society, told Cointelegraph.
“Without decentralized, centralized, error-prone systems, they will pull us out of the abyss, especially with AI,” he said.
Source: VanEck
Related: AI memecoins will become utility tokens
A million AI agents
As of December, Web3 hosts about 10,000 AI agents, earning millions of dollars from onchain activities every week, according to VanEyck's report.
The asset manager expects more than 1 million AI agents to populate blockchain networks by the end of 2025.
“The potential universe of AI agents interacting with crypto is limitless,” Matt Hogan, Bitwise's head of research, told Cointelegraph.
In the year By 2024, tokens tied to the agency's AI will increase to more than $10 billion in market capitalization, especially in Q4, according to CoinGecko.
The agency's AI projects include AI16z, a platform for launching AI agents on Coinbase's Base network, and aims to guide onchain investments.
Source: daos.fun
Early use cases
Storing cryptocurrency on behalf of human token holders is an early potential use case for agency AIs, Hugan told Cointelegraph.
We see many attempts, but only a few stick. AI agents that engage in stalking, for example, seem like a logical first step,” Hugan said.
Staking involves validating the blockchain network by locking tokens with validators to cut transaction fees.
Meanwhile, ai16z agent Eliza, who autonomously manages an onchain liquidity pool, is estimated to account for more than 60% of annual revenues, according to data from daos.fun.
Still, onchain AI models lag centralized counterparts like OpenAI's ChatGPT on technical metrics like speed and computing power, Casey said.
Creating effective decentralized AI agents depends on finding decentralized solutions to ensure high-quality training data while protecting user privacy, Serafin said.
Meanwhile, “AI faces increasing pressure to be regulated, and big players like OpenAI are scrambling to find rules that match their own models,” which could hurt decentralized AIs, Casey added.
For investors, “it's okay not to know exactly what's going to happen as long as you understand the importance and expose yourself to risk,” Haughan explains.
Related: Why tech giants like Amazon may be hesitant to accept Bitcoin
