On AI Agents: Not Every Great Equalizer Needs a Scythe

My career began in the financial heart of London, and I’m grateful for everything I learned there. The reasons I left are many - among them, I realized that employees build value for others, so I chose to dedicate my 20-hour days to creating something of my own, where I could reap the rewards and shape the vision. But here’s another: information asymmetry.

For well over a century, institutional investors and insiders have dominated markets by hoarding superior information, such as exclusive access to data, research, or insider tips. Retail traders are often left guessing and essentially gambling more than they can afford to lose. Fortunately, the winds of change are upon us, as AI agents emerge to democratize access to insights once reserved for the elite aka your engineer-turned-banker of a cousin who is doing so well. These automated financial assistants are no longer a luxury but a necessity for survival in modern markets.

This isn’t a new phenomenon. Nobel laureate George Akerlof explored it in his 1970 paper, The Market for Lemons, showing how uneven access to information distorts markets and drives inefficiencies. In finance, it’s simple: when hedge funds know more than retail traders, the game isn’t just unfair - it’s rigged. Legacy institutional players use tactics like front-running (exploiting advance knowledge of trades) or insider trading (acting on non-public data). High-frequency trading firms have microsecond advantages to outpace retail investors. If you were playing poker and could see everyone’s cards, you’d always win. More money for you? Yes. Did you cheat? Also yes.?

AI agents can be the new market equalizers, fed with delicious algorithms that analyze data faster than any human. They digest news, earnings reports, and social media trends to predict market moves, like having a supercharged financial analyst in your pocket. Platforms like QuantConnect now offer retail traders AI-driven tools once exclusive to Wall Street. Even apps like Robinhood integrate machine learning to suggest trades, putting institutional-grade strategies in everyday hands.

AI is crushing information gaps with real-time insights by processing terabytes of data in seconds, from geopolitical events to TikTok trends impacting meme stocks. For instance, during the 2021 GameStop frenzy, retail traders used AI sentiment analysis to coordinate buys. Predictive power allows machine learning models (like XGBoost) to forecast stock movements by identifying patterns invisible to humans. Imagine predicting a market crash weeks in advance. Take that, TradFi!

Retail investors now use AI-powered dashboards to track insider trading patterns or earnings surprises, tools that cost millions just a decade ago.

BUT where there is light, there is darkness, so let's talk about risks. As most of us learned in our very first high school economics class - there is no free lunch. While AI could make markets more efficient by spreading information, doing so would also amplify volatility. Thousands of AI bots react simultaneously to a news headline? Expect wild price swings.

It's crucial to remember and understand that AI is only as good as its data. Biased or incomplete datasets (e.g., ignoring emerging markets) could lead to flawed predictions. Also, who’s accountable if an AI manipulates markets? Current regulations lag behind tech advances, creating loopholes for abuse. Remember the 2010 Flash Crash? Overdependence on algorithms can backfire...fast. If we don’t get ahead of these risks, AI won’t democratize finance, it will just create new kings.

In order to avoid a new era of "algorithmic inequality" and, with it, even greater information asymmetry, we need transparent AI models to prevent hidden biases, updated regulations to keep pace with tech, and human-AI collaboration to ensure oversight. Even bots need oversight; just ask Zillow. Their AI overpaid for thousands of homes, misjudged market trends, and tanked their entire homebuying business with a $500 million loss.

I'll leave you with the questions that keep me up at night. Can we truly expect a fairer, more democratic future? Given how few real democracies exist, I’m skeptical, but decentralization, by design, tilts the scales toward fairness. As AI agents reshape financial markets, will we harness them as tools of equity, or will they become yet another instrument of the privileged few?

The future of financial fairness isn’t preordained; it lies in the choices we make today.