Making Markets More Human, Not Less

NEW YORK, NEW YORK – APRIL 03: Stock market numbers are displayed on the floor of the New York Stock Exchange during morning trading on April 03, 2025 in New York City. The stock market opened up with all three major stock indexes going under as the market reacts to U.S. President Donald Trump’s announcement of sweeping tariffs of at least 10% and even higher for some countries. At opening the Dow dropped 1,500 points, S&P 500 lost 4% and the Nasdaq Composite slid 5%. (Photo by Michael M. Santiago/Getty Images)

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The statistics are brutal and unchanging: 90% of retail traders lose money. Despite decades of technological advancement, sophisticated charting tools, and instant access to market data, the failure rate remains stubbornly consistent. Most assume artificial intelligence will solve this by removing human emotion from trading entirely. The reality unfolding across trading platforms tells a different story: AI is making trading more human, not less.

How AI Can Help With The Emotional Trading Trap

Ben Bilski has seen the carnage firsthand. The former professional swimmer turned serial entrepreneur built NAGA into a 2 million client brokerage before exiting in 2023. Running a platform where people trade with leverage taught him something counterintuitive about market failure.

“There is a specific period of time where every trader has a grip on the market,” Bilski explains. “They feel the flow, understand the charts, and have consistently great results. But there are these one or two days where the trend changes, where you lose your streak, and the drawdowns are so large that they mess up your stats.”

Bilski believes that the problem isn’t just knowledge. Many traders understand risk management, position sizing, and technical analysis. The breakdown happens when emotions take over during those crucial moments. Revenge trading after a loss. Holding positions too long. Ignoring their own risk rules when they see charts moving against them.

Traditional solutions miss the mark. Courses teach theory. Coaches aren’t available 24/7. Even the most disciplined traders occasionally crack under pressure.

The Social Media Illusion

The rise of trading influencers on social media created another layer of confusion. Traders scroll through feeds filled with screenshots of massive gains, hot takes on market direction, and expensive lifestyle posts funded by trading profits. But separating authentic advice from performance theater became nearly impossible.

“It’s harder than ever to understand what’s real and what isn’t,” Robinhood acknowledged when announcing Robinhood Social at their September summit. The platform’s solution: verified trades displayed in real-time, authentic trader profiles backed by know-your-customer verification, and actual performance metrics instead of cherry-picked screenshots.

The social element isn’t going away. If anything, organic interest in trade journaling recently hit an all-time high as traders search for authentic ways to improve their performance. But the evolution toward verified, accountable social trading represents a fundamental shift from influence-driven speculation to data-driven learning.

The AI Advantage in Human Psychology

This is where AI enters the picture, not as a replacement for human judgment, but as a real-time psychological monitor. Bilski’s new platform, True Trading, embeds AI directly into the trading process as what he calls a “24/7 trade companion.”

The AI doesn’t make trading decisions. Instead, it watches patterns: How often does a trader adjust stop losses? Are they overexposed relative to their account size? Does their current behavior match previous sessions that ended in significant drawdowns?

“The AI can connect to your account, see exactly all your positions, what you traded, how you trade, when you log on, what you do,” Bilski describes. “Imagine this companion constantly giving you not direct advice, but going into your subconscious mind and saying something’s going on here. Greed is taking over, fear is taking over.”

The approach acknowledges trading’s fundamental reality: success depends more on psychological discipline than market prediction. An AI that can spot emotional patterns in real-time offers something no course or coach can provide – immediate intervention at the moment discipline breaks down.

Preserving Human Learning

The challenge becomes how to add AI assistance without removing the friction that makes learning possible. Andrew Michael, head of growth at TradeZella, faces this dilemma directly. The trade journaling platform, founded by trading educator Ummar Ushraf, has helped thousands of traders develop the disciplined analysis habits that separate winners from losers.

TradeZella’s data tells a compelling story. While 90% of traders generally lose money within 90 days, 67% of TradeZella customers are profitable after six months. The difference: systematic journaling and analysis of every trade.

But AI threatens to undermine this advantage. “The main AI benefits like auto-generated content and summaries risk removing the valuable friction that makes journaling effective for learning,” Michael notes. The manual process of writing down what happened, why a trade worked or failed, and what to do differently forces traders to confront their mistakes honestly.

The solution involves using AI to enhance rather than replace human analysis. Instead of auto-generating trade reviews, AI can highlight patterns across multiple trades, suggest questions for deeper reflection, or identify blind spots in a trader’s self-assessment.

From Performance Theater to Real Accountability

Robinhood Social’s verified approach represents a broader shift in trading culture. The platform tracks one-year and daily profit and loss, profit rates, and detailed trade histories for users who choose to share their performance. Unlike social media screenshots, the data comes directly from actual trading accounts.

The social features extend beyond individual traders. Users can follow “insiders, hedge funds, and politicians” based on publicly reported trades, connecting retail traders with institutional-level market intelligence previously accessible only to professional investors.

This creates a new dynamic where influence derives from verified performance rather than follower count or engagement metrics. The change could fundamentally alter how trading education and advice distribution works online.

The Copy Trading Evolution

Social trading isn’t new, but AI amplifies its potential. Bilski describes “social AI trading” where users can follow algorithmic profiles that trade based on specific strategies. Unlike human traders who might deviate from their stated approach, AI profiles maintain consistent discipline.

“You can follow a profile that specifically focuses on shorting the market,” he explains. “It doesn’t exist like that now, but it has its own capacity and focuses on that part. The profile can talk to you, share pictures, share voice notes.”

These AI trading profiles could solve the authenticity problem that plagues human influencers. An algorithm following a momentum strategy will consistently follow momentum signals without the emotional deviations that cause human traders to abandon their methods during drawdowns.

The Human-AI Partnership

The emerging picture isn’t AI replacing human traders, but AI serving as the disciplined partner most traders lack. The technology excels at pattern recognition, emotion detection, and consistent rule following – exactly the areas where humans struggle most.

True Trading’s approach of monitoring behavior without making decisions preserves human agency while providing psychological guardrails. TradeZella’s challenge of adding AI insights while maintaining learning friction demonstrates the thoughtful integration required. Robinhood Social’s verified performance data creates accountability previously impossible in trading education.

The combination suggests a future where technology doesn’t eliminate human judgment from trading but makes human judgment more reliable. AI becomes the voice of discipline when emotions threaten to derail careful planning. Social features create genuine learning communities based on actual results rather than marketing theatrics.

Measuring Success Differently

The true test will be whether these human-AI partnerships can improve the industry’s dismal success statistics. Early indicators seem promising. TradeZella’s 67% profitability rate among customers shows what systematic analysis can achieve. True Trading’s approach of preventing emotional mistakes could address the specific moments when traders typically destroy their accounts.

But the broader transformation may be cultural. As verified performance data becomes standard and AI helpers provide real-time discipline coaching, trading could evolve from a largely solitary struggle against market forces and personal psychology into a more collaborative, evidence-based practice.

The paradox of AI in trading continues to unfold. Rather than creating emotionless algorithmic trading, artificial intelligence is making the human elements of trading – psychology, learning, community, and accountability – more central than ever. The technology succeeds not by replacing human judgment, but by making human judgment more reliable when it matters most.

For an industry where 90% of participants have historically failed, any improvement in human decision-making could represent a fundamental shift. The early evidence suggests AI’s greatest contribution to trading won’t be superior market predictions, but helping humans trade more like the disciplined, consistent professionals they aspire to become.