AI Agents Take Over Base: 95% of Payments Now Exceed $1

Chainalysis data shows AI agents on Base now drive 95% of payments over $1, signaling a shift from micro-testing to a real autonomous economy.

Data from Chainalysis reveals that transfers valued at over $1 now account for 95% of the total value of agentic payments on Base. Just one year ago, such operations were virtually non-existent, with most transactions limited to micro-payment testing at minimal values.

This shift suggests that autonomous software systems are increasingly gaining access to real-world financial operations. Rather than merely performing basic tasks like requesting API services or automated micro-payments, agents are beginning to manage more complex processes—ranging from bookings and purchases to executing business services and coordinating digital workflows.

Base Becomes Infrastructure for the AI Economy

The rapid growth of these operations is no coincidence. Base, developed by Coinbase using Ethereum technology, offers significantly lower transaction costs and nearly instantaneous settlement. These specific characteristics make it ideal for automated systems that need to perform a high volume of operations without human intervention.

Traditional payment systems struggle to service such a model. Bank transfers, card payments, and most existing financial networks were built for interaction between humans and companies, not autonomous software agents. High fees, limits on payment frequency, and a lack of programmable rules make these solutions inefficient for the new generation of AI applications.

Consequently, more developers are building “agent-native” infrastructure—an ecosystem where AI agents can independently purchase services, manage budgets, and interact with other systems using stablecoins like USDC.

This trend is already surfacing beyond the crypto industry. Companies in travel, e-commerce, and cloud services are experimenting with models where AI agents handle automatic payments for reservations, software services, and data access.

The Next Challenge: Trust

As volumes increase, so do concerns regarding security. Analysts warn that the entry of autonomous agents into financial systems requires an entirely new approach to risk control.

Key solutions being developed by the industry include programmable spending limits, cryptographic restrictions on agent actions, and identification systems that link every AI action to a specific user or organization.

The topic is also catching the attention of regulators. Existing financial rules were designed for payments made by individuals or legal entities, not autonomous algorithms. This creates a legal vacuum regarding liability for errors, fraud, or unauthorized actions by AI systems.

Despite these risks, the growth on Base demonstrates that the concept of an “agentic economy” is moving from theory to practice. For the blockchain industry, this could prove to be the next major growth driver following DeFi, NFTs, and the tokenization of real-world assets.

While investors have primarily bet on AI infrastructure in recent years, latest data reveals that real economic activity is forming, where AI not only analyzes information but also independently conducts financial operations. This development could reshape how software interacts with the global economy over the next decade.