By 2025, the rise of artificial intelligence (AI) agents will redefine the Web3 landscape, with staking and on-chain transactions of crypto assets becoming major use cases.
As Cointelegraph reported, industry experts expect these autonomous systems to play a key role in the decentralized community despite challenges such as technical limitations, regulatory hurdles, and concerns about centralization.
Artificial intelligence agents, also known as agent-based AI, can operate autonomously to achieve complex goals. These systems are already making waves in the digital economy, developing decentralized applications, launching tokens, and engaging in human-like interactions. According to a report by asset management firm VanEck, blockchain networks could accommodate more than one million AI agents by the end of 2025. Currently, about 10,000 AI agents collectively earn millions of dollars per week through on-chain activity.
Bitwise Research Director Matt Hougan said: "The potential areas for AI agents to interact with Crypto assets are endless. This booming market will witness countless experiments, and some breakthrough applications may become the frontrunners."
Staking of Crypto assets is expected to be one of the earliest and most viable applications of AI agents.
Staking involves locking tokens to protect the blockchain network and earn part of the transaction fees. Hougan noted that “AI agents participating in staking seems to be a logical first step.”
Projects such as ai16z and Virtuals have begun to leverage AI for innovative applications.
ai16z’s agent Eliza autonomously manages on-chain liquidity pools and reportedly has an annualized return of over 60%. Similarly, Virtuals provides a platform for deploying AI agents on networks such as Coinbase’s Base.
Despite the promising prospects, decentralized AI agents still face significant obstacles.
Michael Casey, co-founder of the Decentralized Artificial Intelligence Association, highlighted the risks of centralized systems dominating the field of artificial intelligence, warning that "without decentralization, a dysfunctional system could lead to catastrophic consequences."
In addition, decentralized AI models currently lag behind centralized models such as OpenAI's ChatGPT in terms of speed and computing power.
JD Seraphine, Web3 AI developer at Raiinmaker, explained: "Creating viable decentralized AI agents depends on developing solutions that both ensure high-quality training data and protect user privacy."
At the same time, regulatory pressure is also enormous. Casey noted that “major players like OpenAI are lobbying for rules that favor their centralized model, which could be detrimental to decentralized AI initiatives.”
As the Web3 ecosystem grows, the integration of AI agents could open up unprecedented possibilities.
Investors and developers alike are keen to explore this emerging space. Hougan succinctly sums up the sentiment: “It’s OK to not know exactly what’s going to happen, as long as you recognize the importance and are prepared for exposure.”
The rapid development of AI technology, coupled with the decentralized ethos of Web3, sets the stage for an era of transformation. While challenges remain, the potential for AI agents to reshape the digital economy is undeniable.
By 2025, these autonomous systems could become an integral part of blockchain networks, driving innovation and efficiency across the ecosystem.
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