The average retail investor still faces a daunting uphill battle when it comes to beating the stock market. Despite decades of financial education campaigns, new digital tools, and the explosion of investing content on social media, the odds haven’t moved much in favor of individual players.

Numerous studies confirm this. A consistent body of academic literature—including work by finance professor Terrance Odean at the University of California, Berkeley—has shown that individual investors tend to underperform the broader market. The reasons vary, but common culprits include high fees, emotional decision-making, and a lack of risk management discipline.

But some argue that the landscape is finally starting to shift.

“People love to glorify gut instinct in the market, but instincts are just bias wearing a confident face,” says George Kailas, CEO of Prospero.AI, a platform that uses machine learning to analyze market activity for retail investors. “Machine learning doesn’t care about headlines, hunches or hype; it simply analyzes millions of data points in real time to find statistical relationships at scales the human brain cannot comprehend.”

That ability—to see patterns buried in the noise—is what Kailas and others believe could give individual investors the edge they’ve long lacked. He adds: “The truth is, intuition might feel right, but the market isn’t built on feelings. It’s built on math.”

It’s a provocative claim, and one that taps into a longstanding debate: Can regular investors really beat the market?

A Game Stacked Against You

Analysts like David E. Y. Sarna, author of History of Greed, caution that beating the market consistently is rare, and likely not achievable without taking on substantial risk. “I don’t think anyone can consistently outperform the S&P 500 without assuming greater than market risk,” he told Investopedia.

Others, such as financial author Todd Tresidder, argue that retail investors shouldn’t aim to beat the market at all—instead, they should focus on losing less. “Big investors are the market, but the little guy is nimble,” he says. That nimbleness, combined with systematic risk management, may allow investors to achieve similar or slightly better returns with lower risk exposure.

Even proponents of active investing, such as retirement strategist Robert Laura, admit the cards are stacked against the average person. Most are stuck in 401(k) plans with limited fund choices and high fees. Others buy into mutual funds that mirror market indices, which leaves little room for outperformance. Meanwhile, many investors remain overconfident in their ability to react to market news—what’s often called “headline risk”—without a disciplined plan.

Where AI Could Step In

That’s where Kailas believes artificial intelligence can level the playing field.

While machine learning tools are widely used in hedge funds and quant trading firms, the idea of bringing those same capabilities to retail investors is still relatively new. Platforms like Prospero.AI aim to change that by offering data-driven insights that don’t rely on human emotion.

The promise is not just automation, but augmentation—giving investors better tools to make their own decisions. AI can help flag patterns that suggest a security is overbought or detect unusual options activity that might hint at future price movement. When paired with human judgment and a disciplined investment strategy, these tools can offer the kind of edge that has historically been the domain of professionals.

Of course, there are limitations. AI tools don’t eliminate risk, and they aren’t foolproof predictors. But their strength lies in their consistency—they don’t deviate from process based on fear, greed, or a flashy news headline.

The Bottom Line

The question of whether retail investors can beat the market isn’t going away. For many, it’s more than a financial challenge—it’s a philosophical one. Can the playing field ever be truly level when institutions have more capital, more data, and more leverage?

Perhaps not entirely. But as machine learning becomes more accessible and platforms evolve to empower individual users, the margin of disadvantage may shrink. The key, according to Kailas, is not replacing human judgment with algorithms—but refining that judgment through better tools.

In today’s fast-moving market, the difference between outperforming and underperforming may come down to one thing: how well you can cut through the noise. And in that regard, data—not instinct—may be your most valuable asset.