Gate founder and CEO Dr. Han has backed a human-led approach to crypto trading as millions of digital assets and tens of thousands of decentralized applications make Web3 increasingly difficult for users to navigate.
Summary
- Gate CEO Dr. Han says AI will support traders without replacing human judgment.
- Gate is integrating AI tools to simplify trading and lower Web3 entry barriers.
- U.S. scrutiny of Chinese AI models could complicate the technology’s global adoption.
In the latest episode of the Gatecast podcast, Dr. Han argued that artificial intelligence could help traders gather information, study market signals, and make decisions without removing the need for human judgment.
According to the Gate CEO, the combination of AI tools and human intelligence could offer a more effective model for trading than relying entirely on automated systems. AI can process large volumes of market information quickly, he noted, but traders must still assess that information before acting.
“AI + human intelligence” will become a more effective approach in the future, Dr. Han said.
His comments place AI in an assistant role at a time when exchanges and traders are using automated tools to scan prices, track market activity and filter information. Rather than presenting the technology as a replacement for users, Dr. Han described it as a way to reduce the effort required to find and understand crypto products.
Gatecast’s discussion also covered the difficulty of entering Web3 when users must choose among millions of tokens and tens of thousands of DApps. Dr. Han identified those choices, along with the learning required to use decentralized products, as barriers that keep potential users outside the sector.
Under his assessment, AI could become a gateway between users and the Web3 ecosystem by helping them locate relevant services and understand how those products work. Intelligent interfaces could also reduce the time users spend researching separate protocols, assets and trading tools, according to Dr. Han.
AI tools will support trader decisions
Gate is already developing several products under what the exchange calls its Intelligent Web3 strategy. Dr. Han identified Gate AI, GateClaw and Gate for AI Agent as parts of a product system designed to integrate artificial intelligence into the company’s trading ecosystem.
Through these services, Gate is using AI to simplify product interactions and reduce the amount of knowledge required before users can begin exploring Web3, according to the CEO. Dr. Han added that the exchange plans to continue developing intelligent products that make decentralized services easier to access.
His position differs from predictions that increasingly capable models could eventually remove people from financial decision-making. While Dr. Han credited AI with improving research and signal analysis, he maintained that the technology cannot fully reproduce the judgment traders apply when interpreting market conditions.
Earlier this week, Binance founder Changpeng Zhao also separated AI’s economic role from that of Bitcoin. In an X post, CZ argued that artificial intelligence can raise productivity, improve business efficiency and support technological development, while Bitcoin offers a scarce asset that cannot be expanded beyond its 21 million-coin limit.
The comparison followed JPMorgan CEO Jamie Dimon’s forecast that the AI investment cycle could attract $725 billion this year. According to CZ, companies developing AI products can issue more shares or raise capital to finance expansion, potentially diluting existing investors, whereas no company or government can increase Bitcoin’s programmed supply.
CZ also rejected the idea that rapid progress in artificial intelligence gives investors the same protection that Bitcoin may offer when fiat currencies lose purchasing power. His comments focused on the difference between investing in productivity-driven businesses and holding an asset designed around fixed supply.
Political pressure could complicate AI adoption
Dr. Han’s case for AI-assisted Web3 access comes as Washington considers how foreign models should operate in the U.S. market. As previously reported by crypto.news, parts of the Trump administration have discussed de facto restrictions on Chinese open-source models after Moonshot AI’s 2.8-trillion-parameter Kimi K3 topped a major coding leaderboard.
Axios reported that American companies have shown interest in Chinese systems because they can provide capable performance at lower prices. Open-weight models also allow businesses to download trained parameters, operate models on private servers and modify them without depending on the original developer’s platform.
People involved in the U.S. policy debate have previously considered placing Chinese AI laboratories on the Commerce Department’s Entity List, according to the crypto.news report. Such a designation could restrict access to American technology without government licenses, although earlier proposals were paused amid concerns that the restrictions could slow AI development in the United States.
Political scrutiny increased on July 22 when Michael Kratsios, director of the White House Office of Science and Technology Policy, accused Moonshot AI of using Anthropic technology to develop Kimi K3. In an X post, Kratsios claimed that information obtained by the U.S. government linked K3’s development to Anthropic’s Fable model.
Kratsios alleged that Moonshot created an internal platform capable of extracting knowledge from American models through large-scale distillation. He also claimed that the platform could change its access methods quickly, making the alleged activity harder for U.S. developers to identify.
However, the White House official did not release technical records or other evidence supporting the allegations. Moonshot AI had not publicly responded at the time of the report, while the White House had not provided material that independent researchers could use to determine whether K3 incorporated Anthropic’s proprietary technology.
Despite those policy disputes, Dr. Han expects AI to play a growing role in how users discover and operate crypto products. Gate’s strategy keeps traders responsible for the final decision while assigning AI the task of organizing information, identifying signals, and lowering the technical barriers surrounding Web3.
