I’ve been thinking about an unintended consequence of using AI for investment research.
I previously wrote about how your algorithm is your portfolio. Your social media feed has too much control over where you attention goes, so prune your feed carefully.
Your social media feed is also planting investment ideas in your head.
You see a ticker mentioned on X, Substack, and Reddit… and next thing you know, you have ChatGPT or Claude running a comprehensive investment analysis. And so is everyone else.
How stocks end up on your watchlist
Most individual investors don’t have a formal process for finding companies to research. They tend to add stocks to their list to research as they hear about them.
Once social media enters that equation, it introduces a certain selection bias.
Recommendation algorithms decide which content gets distributed based largely on what people engage with. And the AI models running you investment analyses are trained of this data.
The stocks getting the most attention are the most controversial ones. Not necessarily the ones that present the best investment opportunity.
FINRA’s 2024 investor survey found that 26% of investors use recommendations from social media influencers when making investment decisions. Among investors under 35, that figure rises to 61%. Stunning, and, the death of traditional equity research.
There are thousands of publicly traded companies. How many of them have you never considered simply because they never came up in your social media feed?
AI is remarkably good at researching popular stocks
I recently wrote about a study testing how AI models manage stock portfolios. Researchers tracked the stock selections of ChatGPT, Claude, Gemini, and Grok.
The resulting portfolios had about 41% allocated to semiconductor stocks, compared with roughly 20% in the S&P 500. The models tend to favor companies dominating the headlines. They constructed portfolios with significantly more risk than the general market.
Keep in mind that the study covered just eight months during a particularly strong market. It’s not proof that AI will always favor the most popular stocks.
But the results are worth noting.
We have tools capable of analyzing enormous amounts of financial information, yet their recommendations can end up looking suspiciously similar to whatever investors are already excited about.
There’s a reason for this. AI models learn from information that already exists. Popular companies have an abundance of articles, analyst reports, interviews, and online discussions available for the models to draw from.
A company with limited analyst coverage may have excellent financial statements but relatively little written about it. Unless the research process deliberately searches for these businesses, it’s easy for them to be overlooked.
That strikes me as a missed opportunity.
Finding the next investment
In my current investment research process, I look for companies with durable competitive advantages, a long runway for growth, and valuations that don’t already assume everything will go perfectly.
I’m particularly interested in businesses that have room to become materially larger over the next five years.
I’ve been using a stock screener to make a short list of companies that have the characteristics I’m interested in, and using different AIs to debate the merits of each. You can learn more about my current process here.
Popularity isn’t an investment thesis
I made 34x on Applied Digital after holding an unpopular investment thesis for about a year and a half. The market had largely written off the company, but I saw potential.
I’ve also invested in emerging technologies that later became wildly popular. In 2022, I bought publicly traded quantum computing companies with the intention of holding them for 20 years. By 2025, some of those stocks had appreciated around 50x. I sold because the valuations had gotten far ahead of the underlying businesses.
Being early matters, but so does recognizing when the opportunity has already been priced in.
I’m not opposed to investing in popular companies. Nvidia is an obvious example of a stock that rewarded investors despite years of attention and increasingly high expectations. Popularity alone tells you little about whether a stock is attractive.
The issue is how we decide which businesses deserve our attention.
AI has made it easier than ever to research practically any company. I think individual investors should take advantage of that by expanding their search beyond the stocks they already know.
Otherwise, we’re using extraordinary technology to research the same handful of companies that the internet was going to tell us about anyway.