By 2025, Web3 is poised to undergo a dramatic transformation, spurred by the emergence of over a million AI agents.
These digital entities are expected to focus primarily on cryptocurrency staking and on-chain trading, as highlighted by industry experts in a recent Cointelegraph report.
Emergence of AI Agents in Web3
These AI agents are already beginning to carve out their niche in the digital marketplace.
They are actively involved in building Web3 applications, generating tokens, and engaging independently with users, demonstrating their potential to autonomously pursue complex goals.
J.D. Seraphine, a developer specializing in Web3 AI at Raiinmaker, believes these agents will play increasingly vital roles within decentralized communities by 2025.
However, he warns of several challenges ahead, including technical hurdles, regulatory landscapes, and the risk of centralization.
Michael Casey, co-founder of the Decentralized AI Society, shares these concerns and points out that centralized systems could lead to negative outcomes, particularly for AI.
Current Landscape and Future Projections
Currently, the landscape features roughly 10,000 active AI agents in Web3 that, according to a VanEck report, are generating millions of dollars weekly through various blockchain activities.
By the end of 2025, this number is projected to soar past one million.
Matt Hougan, head of research at Bitwise, emphasizes the vast potential for AI agents to tap into the cryptocurrency market, describing this potential as nearly boundless.
Over the past year, tokens linked to agentic AI reached a market capitalization exceeding $10 billion, primarily driven by last quarter’s performance, according to CoinGecko data.
Initiatives like ai16z and Virtuals illustrate the innovation occurring in this field. ai16z seeks to harness AI for on-chain investments, while Virtuals provides a framework for deploying AI agents on Coinbase’s Base network.
Hougan believes it makes perfect sense for these agents to manage cryptocurrency staking on behalf of human token holders, considering this presents a logical first application of their capabilities.
Challenges and Considerations
Staking involves users locking tokens with validators to support a blockchain and earn a portion of transaction fees.
For instance, the ai16z agent named Eliza oversees an on-chain liquidity pool and has reportedly achieved impressive annualized returns exceeding 60%, as per data from daos.fun.
However, on-chain AI models still lag behind centralized counterparts such as OpenAI’s ChatGPT in processing speed and computational power.
Seraphine notes that for decentralized AI agents to succeed, it’s crucial to find innovative ways to gather high-quality training data without compromising user privacy.
Additionally, Casey points to the growing demand for regulation in the AI space.
He observes that key players like OpenAI are lobbying for rules tailored to their own models, potentially sidelining decentralized AI efforts.
For investors, Hougan suggests that while the future may be uncertain, understanding the transformative potential of these developments is key.
Strategically positioning oneself to capitalize on emerging opportunities is essential, especially in this rapidly evolving landscape.
Source: Cointelegraph
