Binance founder CZ: AI agents may give rise to crypto-native microtransactions
Changpeng Zhao (CZ), founder of Binance, said in an interview with Japanese business media outlet PIVOT that in the future each person may have hundreds, thousands, or even millions of back-end AI agents, responsible for tasks such as video editing, publishing, marketing, and collecting payments, and that these agents will carry out a large number of transactions. CZ said AI agents will not use credit cards or bank accounts, and that the ideal solution is digital-native currency (cryptocurrency).
CZ said AI may increase transaction speed and volume by about 1,000 to 1 million times, and transaction sizes may be smaller, such as paying 1 yen to watch a video rather than buying a fixed subscription. He also said AI will need digital authentication and verification, and these functions should be handled by blockchain. CZ suggested that the Japanese government further digitize, and said that AI and blockchain will make society more efficient and economic transaction volume larger.
CZ also encouraged young people in Japan to engage in AI and blockchain startups, saying that today is the best day in history to start a business or build, better than any day in the past. He pointed out that under the new environment, Japan’s traditional lifetime employment system is worth reexamining; the startup path has great uncertainty and more pain, but the rewards, positive impact, and financial gains are also greater, and AI makes starting a business easier.
Original sources:
Title: 【Japan exclusive interview: Binance founder CZ】What is the revolution of “AI × blockchain”? / What the billionaire after serving time is betting on next / Changes that will come within 5 years / What Japanese companies should prepare for now [PIVOT GLOBAL] Publisher: PIVOT Official Channel Publication date: 2026-10-24 URL: https://www.youtube.com/watch?v=6hmlgUN-42E Source nature: original interview (video transcript) Verification status: This time, the relevant transcript segments on the actual YouTube page were read, including statements on the number of AI agents, transaction speed and volume increases, 1-yen microtransactions, digital-native currency, authentication and verification, etc.; verification date 2026-10-25 Supported content: supports CZ’s specific statements in the body about AI agents, transaction speed and volume, microtransactions, the ideal solution of cryptocurrency, and blockchain handling digital authentication
Title: Great chat with @sakiko_noji on @PIVOT_inc_ about AI, blockchain, and why today is the best day in history to build. Publisher: CZ 🔶 BNB (@cz_binance) Publication date: 2026-10-24 URL: https://x.com/cz_binance/status/2113816404856299679 Source nature: post by the person concerned Verification status: The post content was actually read this time, verification date 2026-10-25 Supported content: supports CZ’s own confirmation that the interview involved AI, blockchain, and the statement that today is the best day in history to build
ABAB AI Insight
After stepping back from Binance’s day-to-day operations, Changpeng Zhao has repeatedly emphasized in public interviews the combination of AI agents and cryptocurrency. In his early years, he developed software in Tokyo for systems related to the Tokyo Stock Exchange, giving him direct technical experience with trading systems; when Binance was founded in 2017, he also briefly moved the team to Japan. In recent settings, such as Davos and multiple podcasts, he has likewise pointed out that AI agents cannot naturally use credit cards or bank accounts, because traditional payments rely on manual authentication and API restrictions, whereas blockchain is more suitable by design for programmatic interaction.
If AI agents operate at the scale CZ describes, payments will shift from a model of human-initiated, bank-intermediated, fixed subscriptions to one of machine-autonomous, high-frequency, pay-per-use billing. Funds will no longer mainly flow into the traditional card network and bank account system, but into a programmable crypto settlement layer; 1-yen-level microtransactions are commercially viable only in an environment with extremely low settlement costs and no need for manual confirmation. CZ also places authentication and verification within the scope of blockchain, meaning identity, permissions, and payment confirmation may be completed on the same on-chain infrastructure, rather than relying on external KYC processes.
Compared with early internet payments, credit cards and bank accounts are batch settlement systems designed for human users; once the transaction subject becomes millions of autonomous agents, latency, fees, and compliance friction become bottlenecks. CZ’s view this time is consistent with what he said in early 2026 in Davos and other settings, but in the Japan interview he more specifically used the example of watching a video for 1 yen and directly linked it to Japan’s lifetime employment system and young people’s startup choices. The difference is that Japan’s traditional employment model emphasizes long-term stability, while the agent economy may shift more economic activity from fixed employment relationships to on-demand, programmatic task settlement.
If AI agents do in fact adopt crypto-native currency on a large scale, traditional payment institutions’ pricing power and traffic entry points in microtransaction scenarios may be weakened, while public chains or stablecoin networks with low-cost settlement and programmable capabilities will gain new sources of transaction volume. One indicator to watch is whether on-chain microtransaction counts and average amounts continue to decline, and whether agent-related payments begin bypassing traditional card network clearing.
ABAB News · Cognition Law
As AI agents scale up, payment demand shifts from human confirmation to programmatic microtransactions, and the choice of settlement layer changes accordingly.
Traditional banks and card networks are designed for human pacing and cannot naturally accommodate high-frequency, small-value machine settlement.
As AI lowers startup costs, the uncertainty of the startup path forms a more direct contrast with the stability of lifetime employment.