Artificial intelligence is rapidly reshaping the tools brokers offer traders, but it is unlikely to turn novices into market wizards overnight. That was the uneasy consensus – and point of friction – at the Finance Magnates London Summit 2025, where executives from AI firms, data providers, and a regulated broker debated where broker growth will really come from heading into 2026.

The panel, “Your Broker’s Growth Is Elsewhere, 2026 Edition,” centred on a core question confronting the brokerage industry: can AI genuinely improve trading outcomes, or does its real value lie in boosting engagement, retention and monetisation rather than performance itself?

The session brought together voices from across the trading ecosystem to explore how brokers are recalibrating growth strategies amid rapid advances in AI and data. Moderated by Adam Button, Chief Currency Analyst at investingLive, the panel featured Roy Michaeli, CEO of WNSTN AI; Kieran Duff, Head of UK Growth and Business Development at Darwinex; Braden Dennis, CEO of Fiscal.ai; and Dor Eligula, Co-Founder and Chief Business Officer at BridgeWise.

Traders Lag, Tools Race Ahead

Duff struck the most sceptical note. Despite the industry’s AI enthusiasm, he said most retail traders are still struggling with the basics.

“I speak to hundreds of traders a week and not one of them really ever mentions AI,” Duff said. “They’re still learning how to trade. There’s a massive learning curve before you even get to integrating something like AI.”

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For Duff, the hard truth is psychological, not technological. “AI can’t help you manage the emotional trauma of losing a lot of money,” he argued. Even the best tools cannot eliminate fear, greed or overconfidence – forces that ensure most traders fail while a minority succeed.

That realism resonated with the moderator, Button, who noted that markets have always “whittled down” participants until only a few survive. The question, he pressed, is whether AI can soften that brutal funnel.

Education Versus Emotion

Eligula pushed back directly. Drawing on data from more than 35 million end users across 90 brokers and banks, he argued that AI-driven “investment intelligence” can materially change trader behaviour.

“When users feel more educated about the decision they made – even if they lost – they are more likely to come back and try again,” Eligula said. BridgeWise has seen lower churn and higher engagement when users interact with its AI tools before trading, he added.

In one recent deployment with a broker serving 3.5 million users, Eligula said AI-driven insights tied to live events lifted trading volumes by about 15 percent, both in trade count and size. The key, he stressed, is not raw data but interpretation: “Data alone has partial value. You need a layer on top of it.”

Personalisation, Not Chatbots

Roy argued that much of the debate is distorted by a narrow view of AI as a chatbot dispensing answers. The real breakthrough, he said, lies in contextual, personalised support.

“Think of it as a bionic arm,” Michaeli said. “It’s not telling you what to do. It’s empowering you with the right data, at the right time, based on your portfolio and preferences.”

Personalisation, he added, allows brokers to serve different trader archetypes – those who lean on analyst ratings, technical analysis or long-term fundamentals – without crossing regulatory red lines. The challenge is combining engagement with compliance, not choosing one over the other.

The Data Arms Race

If AI is the interface, data remains the fuel. Braden Dennis, CEO of financial data firm Fiscal.ai, highlighted how AI is collapsing long-standing delays in fundamental information. During Nvidia’s most recent earnings, he said, Fiscal.ai processed and standardised the full financials within three minutes – far faster than the one-to-three-day lag traders have historically endured.

“That’s completely changing what’s available,” Dennis said, especially during emotionally charged moments such as earnings season, when retail investors see positions drop 7 or 10 percent and scramble for answers.

He also pointed to demand for highly specific, non-GAAP metrics – Spotify’s premium subscribers, for example – arguing that long-term investors care less about headline EPS than about the numbers that actually drive a business.

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Regulation Shapes the Technology

The panel’s sharpest disagreement emerged around model design. Eligula argued that large language models are ill-suited to regulated finance due to compliance Compliance In finance, banking, investing, and insurance compliance refers to following the rules or orders set down by the government regulatory authority, either as providing a service or processing a transaction. Compliance concerning finance would also be a state of being following established guidelines or specifications. This designation can also encompass efforts to ensure that organizations are abiding by both industry regulations and government legislation. Understanding ComplianceCompliance is a In finance, banking, investing, and insurance compliance refers to following the rules or orders set down by the government regulatory authority, either as providing a service or processing a transaction. Compliance concerning finance would also be a state of being following established guidelines or specifications. This designation can also encompass efforts to ensure that organizations are abiding by both industry regulations and government legislation. Understanding ComplianceCompliance is a Read this Term risks and opacity. BridgeWise instead uses smaller, domain-specific language models that regulators can audit and approve. “LLMs are a black box,” he said. “In our niche, that’s not acceptable.”

Michaeli countered that compliance is not just about model size but about how insights are framed. “You don’t give advice,” he said. “You make people curious enough to ask the next question – within the rules.”

What Growth Really Looks Like

By the session’s end, one point was clear: broker growth is less about making traders smarter overnight and more about keeping them engaged, informed and emotionally resilient. AI’s commercial impact, panelists agreed, is already visible in higher retention, increased trading activity and better alignment between broker incentives and user behaviour.

Dennis closed with a reminder that technology cannot rewrite human nature. Citing a well-known Fidelity study, he noted that the best-performing accounts over decades belonged to investors who had either forgotten their passwords – or passed away.

“What does that tell you?” Dennis asked. “Investing rewards patience and good behaviour. It’s done with your stomach, not your brain.”

For brokers chasing growth into 2026, the message was sobering but pragmatic: AI may not stop traders from making mistakes, but it can help them understand those mistakes – and stick around long enough to make the next trade.