**[Analysis: AI Trading Agents May End High-Frequency Trading Models on Exchanges, Bringing Fair Incentives to Retail Investors]** Odaily Planet Daily News – With AI trading agents entering the financial markets, the structural issues of retail trading are potentially undergoing a transformation. The current business model of exchanges and brokers relies on frequent trading by customers, profiting through commissions, spreads, and order flow regardless of gains or losses. Research shows that 74% to 89% of retail traders ultimately lose money, while the payment for order flow (PFOF) mechanism behind zero-commission trading disconnects platform profits from customer returns. Independent, programmable AI trading agents have the potential to address this structural conflict: by linking agent profits to customer portfolio returns, they encourage disciplined trading rather than trading frequency. These agents can reduce positions, avoid impulsive operations, and protect customer assets in highly volatile markets, achieving true alignment of interests. As the U.S. removes the minimum asset requirement for day trading and the EU prepares to implement a PFOF ban, traditional exchange models are facing regulatory pressure. Meanwhile, AI agents are reconstructing trading frameworks through innovative channels such as on-chain payments, gas-free transactions, and decentralized exchanges, providing retail investors with transparent, fair, and verifiable trading intermediaries. (CoinDesk)