Disciplined AI agents are the disruptor needed to break the exchange churn model

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Disciplined AI agents are the disruptor needed to break the exchange churn model Programmable incentives that allow independent trading agents to earn only when portfolios rise will create a fairer market for retail customers, explains Naja. All within a matter of weeks, Anthropic unveiled new agents for finance, Circle launched nanopayments, MoonPay launched a debit card for agents and Gemini launched agentic trading, signaling the agentic finance fight is here. Whilst the products are new, the underlying business model remains the same. Every exchange and brokerage earns more when customers trade more, and the data on what that does for customer portfolios is unambiguous. Ultimately, agentic rails have arrived faster than incentives have changed. The perverse incentives exchanges hope you miss The conflict is structural to the industry. Brokerages and exchanges don't need customers to win, they need them to keep trading. Crypto exchanges and neobrokers made trading faster, cheaper and frankly, more addictive. The commercial reality is that banks profit when you stay, exchanges profit when you trade, and AI models profit when you prompt. The agent you can trust with your hard-earned capital sits outside all three. An independent agent paid only when the customer’s portfolio wins threatens the current incentive structure of brokerages and exchanges. The truth is, zero-commission trading isn't free. In 2025, U.S. market makers paid more than $4.9 billion for order flow in U.S. equity and options, up from approximately $3.8 billion in 2021 across the 12 largest U.S. brokerages. The same principle applies to crypto. The derivatives volume from Q1 of 2026 reached about $18.6 trillion, 70% of global crypto trading, with perpetuals dominating spot trading. Exchange economics reward trading velocity over disciplined decision-making. At peak, Robinhood relied on more than 75 percent of its revenue from payment for order flow (PFOF), the hidden backbone of "free" trading, in which market makers pay brokers to route customer orders. Every broker using this incentive model needs customers to trade often, even though frequent trading works against long-term returns. Advisory isn’t better. Robo-advisors charge 0.25 percent of assets a year, whether the account is up or down. Human advisors charge around 1 percent, billed against the principal even in down years. The extraction is built into the model by design: the advisor gets paid even when the customer loses. Less exchange friction makes bad trades easier to repeat The harsh truth is that exchanges need customers to trade more, not win. When retail investors lose, the exchanges still get paid. PiP World research found 74% to 89% of retail users lose money trading. Platforms charge at every step, and an AI-enabled exchange could just route you back to the same losing trade faster. The April 14 SEC approval of FINRA's elimination of the Pattern Day Trader rule removed the $25,000 minimum-equity friction. Removing the friction results in more trades, which creates more order flow. More order flow means more money for the broker, whether the customer’s profit and loss (P&L) is up or down. Enter AI agents, paid to improve customer P&Ls The disruptor to this vicious cycle for retail traders is the agent built to do what the existing exchange model avoids: trade less, size down, wait and protect customers from their worst impulses. In volatile markets, the best move is often refusing the bad trade, cutting exposure before emotion takes over. Ultimately, holding discipline when the market wants a reaction. Discipline is hard to sell for an exchange because it shrinks order flow. An agent that earns by protecting customer P&Ls breaks the current incentive model. The next battleground is who profits from the agents' order flow Regulators are squeezing the old "free trading" model. The EU's PFOF ban takes effect June 30, 2026, removing the revenue line behind "free" trades for German and Austrian neobrokers. Trade Republic, a European savings platform, has already found another route to secure a BaFin license to internalize order flow. Whilst TradFi scrambles to patch the leaks, crypto builders are racing to rebuild onchain rails for AI agents. In markets with tiny spreads, fragmented liquidity and millisecond execution, agents transact via nanopayment infrastructure like Circle's protocol. Gas-free trading on perpetual DEX Hyperliquid cuts friction, but maker-taker fees still apply. The real fight ahead isn't who removes friction, but who profits when agents start hammering these frictionless rails with high-frequency trading. Independent programmable agents are better middlemen The exchanges and brokers have spent years making money from customers trading more, understanding less and absorbing tiny costs they barely notice. Every agent built by an exchange will inherit the exchange’s incentives. Would an exchange build an agent that sends trades through a cheaper competitor’s rails? Not voluntarily. Whereas an independent agent has one job: grow and protect the customer’s portfolio, routing trades where they work hardest for the customer. Programmable incentives encoded into smart contracts tie the agent’s incentives to portfolio gains. The customer can see where the money goes, verify what the agent gets paid, when and why. With independent agents, the customer keeps more of the value that used to leak to the exchange through order flow, spread markups and idle-cash interest onto the exchange. The agent is rewarded for disciplined trading, not constant trading. It can trade often when the signal is strong, cut exposure when risk rises and sit out when the market is just noise. The first agentic platform that proves this alignment onchain will give retail investors a fairer counterparty, whose economics finally move in the same direction as theirs. Note: The views expressed in this column are those of the author and do not necessarily reflect those of CoinDesk, Inc. or its owners and affiliates.

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