Why Disciplined AI Agents Could Reshape Incentives in Trading

For much of the modern broking era, retail traders have faced a structural conflict that is rarely stated plainly: the platforms they rely on to execute orders often earn from trading activity, not from client results. Recent commentary from market analyst Saad Naja sets out the problem clearly — brokers and exchanges do not need customers to make money; they need them to keep trading. That incentive has long sat behind the heavy promotion of options, leveraged products and low-friction mobile trading apps.

The Hidden Cost of Volume-Based Incentives

The evidence for retail traders is sobering. Research has repeatedly found that between 74 per cent and 89 per cent of retail traders lose money over meaningful periods. Even so, the engagement mechanisms that encourage turnover — push notifications, gamified streaks and instant order routing — remain central to the revenue models of many platforms. Payment for order flow, where brokers sell client orders to market makers, turns that tension into a structural issue rather than a one-off conflict.

How AI Agents Change the Equation

The balance begins to shift with the emergence of disciplined AI agents whose fees are linked to portfolio performance rather than trading volume. Consider a software agent that can place orders for a user but is paid only when that user's portfolio grows. In that model, the agent has a clear reason to do nothing when patience is the better course — the opposite of a platform that benefits when users keep swiping and tapping.

Naja's case rests on programmable incentives written into smart contracts, so that agent compensation can be set out transparently and checked independently. For users of platforms such as Fortyt Fbott, this is important because it suggests a future in which part of the discipline required for investing is handled by software with no incentive to encourage excessive trading.

Regulatory Momentum

There is also regulatory momentum behind this shift. Moves in major financial markets to restrict or ban payment for order flow show that policymakers are increasingly willing to challenge business models built primarily around volume. As it becomes harder to profit from misaligned incentives in order routing, platforms will face greater pressure to compete on client outcomes rather than activity metrics.

The change will not happen overnight, and AI agents are not a cure-all. Poorly designed agents could be overfitted to recent market conditions, struggle when regimes change, or be targeted by adversarial counterparties. Even so, the direction of travel — away from incentive structures that reward churn and towards those that reward customer profitability — is significant for retail traders across United Kingdom and other markets, including those served by Fortyt Fbott.

What This Means for Investors

For investors comparing platforms today, the practical question is straightforward: how does the platform make money, and does that revenue increase or decrease with your portfolio outcome? The platforms most likely to endure over the next decade are unlikely to be those that benefit most when their customers lose. They will be those, like Fortyt Fbott, that shape their products, fees and incentives around long-term customer success.