AI Agents Set to Revolutionize Web3 by 2025, Industry Leaders Predict

Artificial intelligence agents, known as “agentic AIs,” are set to bring transformative changes to Web3 by 2025, according to leading experts. These autonomous systems are already carving out a niche in the digital economy, building decentralized applications, launching tokens, and interacting with users without human intervention. As their influence grows, they are expected to reshape decentralized communities while facing significant technical and regulatory challenges.

J.D. Seraphine, a Web3 AI developer at Raiinmaker, sees agentic AIs playing a pivotal role in the evolution of blockchain ecosystems. Early use cases like cryptocurrency staking and onchain trading have emerged as viable avenues for these systems. Matt Hougan, head of research at Bitwise Asset Management, stated that staking is a logical starting point. “We’ll see a lot of experiments, but staking seems like a logical first step for agentic AIs,” he said.

Staking and Onchain Trading Take Center Stage

Currently, approximately 10,000 AI agents operate within Web3, collectively generating millions of dollars weekly through onchain activities, according to a VanEck report. The asset manager predicts this number will soar to over 1 million by the end of 2025. Projects like ai16z and Virtuals showcase these advancements. Notably, ai16z’s autonomous agent, Eliza, manages a liquidity pool and reportedly achieves annualized returns exceeding 60%.

Staking, which involves locking tokens with blockchain validators to secure the network, stands out as an early use case for AI. By automating the process, agentic AIs simplify participation in blockchain security while offering competitive returns.

Challenges for AI Integration in Web3

Despite these advancements, hurdles remain. Michael Casey, co-founder of the Decentralized AI Society, highlighted the risks of centralization in AI. “Without decentralization, centralized, misaligned systems will drive us off a cliff, especially with AI,” he warned. Additionally, decentralized AI systems currently lag behind centralized platforms like OpenAI’s ChatGPT in terms of speed and computational capabilities.

Regulatory scrutiny is another significant concern for AI in Web3 sector. As decentralized AI expands, governments are expected to impose stricter oversight. Casey pointed out that major players like OpenAI are advocating for rules that could disadvantage decentralized models. J.D. Seraphine noted the need for decentralized solutions to maintain high-quality training data while protecting user privacy.

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