DIY Investors: Are Americans Using AI to Invest?

Ask a group of self-directed investors how they research a stock today, and you’ll increasingly hear the same answer: they asked a chatbot. What used to mean digging through 10-K filings, screening tools and message boards now often starts with a prompt to ChatGPT, Gemini or a purpose-built investing assistant. The question worth asking isn’t whether Americans are using AI to make investment decisions — they clearly are — but how, and whether it’s actually helping.

The shift is real, and it’s happening fast

Surveys over the past two years consistently show a meaningful chunk of retail investors experimenting with AI. Depending on the study, somewhere between a quarter and a half of DIY investors report using AI tools for at least part of their process. Younger investors lead the pack: Gen Z and millennial traders are far more likely to trust an AI summary than a Baby Boomer who prefers a phone call with a broker.

Most of this activity isn’t happening inside sophisticated hedge-fund software. It’s ordinary people using free or low-cost tools to do things that used to take hours:

• Summarizing earnings reports and quarterly filings in plain English
• Explaining unfamiliar concepts like ETF expense ratios or options spreads
• Comparing two funds or two companies side by side
• Drafting a rough asset allocation based on age and risk tolerance
• Screening for stocks that match specific criteria

Why the appeal makes sense

The draw is obvious. Investing has always come with an information gap between professionals and everyone else. AI tools narrow that gap by making dense material readable and instant. A first-time investor can paste in a paragraph of jargon and get a usable explanation in seconds, without feeling embarrassed to ask a “basic” question.

There’s also a cost angle. Traditional financial advice often carries a 1% annual fee or a high minimum balance. A free AI assistant, or a $20-a-month subscription, feels accessible by comparison. For people with smaller portfolios who mostly want to understand their choices, that trade-off is appealing.

Where AI genuinely earns its keep

AI is strongest as an education and research accelerator. If you use it to understand a company’s business model, learn what a metric means, or organize your own thinking, it can save real time and reduce intimidation. It’s also useful for surfacing questions you hadn’t considered — asking “what are the risks with this investment?” often produces a checklist worth reviewing.

The problems investors keep running into

The enthusiasm comes with genuine hazards, and the people using these tools most aggressively are often least equipped to spot them.

Outdated or invented information. General-purpose chatbots can hallucinate financial data — inventing earnings figures, misquoting prices, or citing a fund that doesn’t exist. Unless a tool is pulling live, verified data, its numbers can be flat wrong or months stale.

Confident-sounding but generic advice. AI is trained to give a fluent answer, not necessarily the right one. It doesn’t know your full financial picture, your tax situation or your actual risk tolerance unless you tell it, and even then it can’t be held accountable the way a licensed advisor can.

No fiduciary duty. A human advisor operating as a fiduciary is legally required to act in your interest. A chatbot has no such obligation and no license. It won’t warn you when you’re about to make a tax mistake or take on more risk than you can handle.

Overconfidence and herd behavior. There’s early evidence that some investors treat AI output as a green light rather than a starting point, leaning into speculative bets because the tool “agreed.” That’s a recipe for chasing hype instead of building discipline.

How to use AI without getting burned

The investors getting the most value tend to treat AI as a research assistant, not an oracle. A few practical habits go a long way:

• Verify every number. Cross-check any figure against a primary source — the company’s filings, your brokerage, or a data provider — before acting on it.
• Use it to learn, not to be told what to buy. Ask it to explain trade-offs and risks rather than to pick winners.
• Give it context. The more you share about your goals, timeline and existing holdings, the less generic the response.
• Prefer tools connected to live data over general chatbots when you need current prices or fundamentals.
• Keep a human in the loop for big decisions — retirement rollovers, large lump sums, tax-sensitive moves.

Where this is heading

The trend line points toward more AI in retail investing, not less. Brokerages are building assistants directly into their apps, and dedicated investing tools are getting better at grounding their answers in real data. Over time, the line between “AI tool” and “robo-advisor” will blur, and regulators are already paying closer attention to how these products present advice.

For now, the honest takeaway is this: Americans are absolutely using AI to make investment decisions, and used well, it’s a legitimate advantage — faster research, clearer explanations, fewer intimidating unknowns. Used carelessly, it’s a fast way to act on wrong information with false confidence. The difference isn’t the tool. It’s whether the investor still does the thinking.