ChatGPT can help organize investment research, but a convincing stock analysis is not evidence that the chatbot can reliably predict returns. A portfolio selected with ChatGPT reportedly performed well during a strong market period; that result alone does not show that the approach will work across different markets or avoid losses. Treat chatbot output as a starting point to verify, not as a crystal ball or a substitute for your own investment judgment.
What “using ChatGPT to pick stocks” actually means
Some investors ask a chatbot to analyze companies or suggest stocks, then decide for themselves whether to place a trade through a broker. That is advisory use: the chatbot produces text, while the investor controls whether to act. It is different from algorithmic trading that automatically executes transactions.
The distinction matters because a chatbot’s answer does not itself manage a portfolio. The investor remains responsible for checking claims, deciding how much risk to take, and making the final trade. Ars Technica reported an eToro survey of 11,000 retail investors worldwide in which 13 percent said they already used AI tools for stock selection and about half were open to considering AI for portfolio decisions. Ars did not state the survey year, and the underlying survey materials are not independently established here.
Why a successful AI-picked portfolio is not proof of prediction
Ars Technica reported that Finder began a 38-stock portfolio selected with ChatGPT in March 2023. By the time of Ars’s September 25, 2025 report, the portfolio had gained nearly 55 percent and outperformed the average of the UK’s ten most popular funds by almost 19 percentage points. The report did not specify the measurement end date or comparison methodology, so those figures should be understood as a reported historical comparison, not a controlled test.
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Market conditions are part of the explanation a reader needs to consider. The Ars article described US stocks as near record levels during the period it discussed. In a rising market, many approaches can show gains; a winning result over one interval does not establish that a chatbot selected the stocks well, that it would beat an appropriate benchmark over other periods, or that it can limit losses when markets fall.
To assess a stock-picking claim, a reader would need more than the final return: the full selection and trading rules, a clearly defined comparison benchmark, fees and any changes to the portfolio, and results across different market conditions. The reported Finder figures alone do not settle those questions.
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What can go wrong with ChatGPT for stock-picking advice
General-purpose AI models generate answers that can sound coherent without being dependable investment analysis. The experts cited by Ars warned that such models can misquote figures and dates, lean too heavily on an existing narrative, and over-rely on past price movements when attempting to predict the future. If an answer gets a filing date, financial figure, or the context around a past price move wrong, its confident tone does not make the underlying claim sound.
Data access is another limitation. A chatbot may not have current information or access to paywalled market data. If it cannot show where a claim came from, or the source is stale or incomplete, the user may be evaluating an analysis built on a partial picture. Current ChatGPT capabilities are not established by the 2025 reporting, so do not assume that any particular version has live, comprehensive market data.
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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →There is also a human risk: investors whose experience comes mainly from a favorable market may mistake gains for evidence that their process is safe. A downturn can expose concentration, volatility, and the limits of an investment thesis. ChatGPT does not remove those risks or make a portfolio appropriate for an individual investor.
How to use a chatbot as a research aid, not a stock tip
If you use ChatGPT to explore an investment idea, make the task specific and check every consequential claim against primary documents. Jeremy Leung’s example prompts, as reported by Ars, include “assume you’re a short analyst, what is the short thesis for this stock?” and “use only credible sources, such as SEC filings.” These prompts can encourage examination of opposing arguments and source quality; they do not guarantee that the response will be accurate or that it has actually relied on the requested sources.
- Ask for analysis questions rather than a buy instruction. Request a bull case, a bear case, and the assumptions that would make each one wrong. Treat the answer as a list of claims to investigate.
- Check facts in the underlying sources. Verify company figures, dates, and statements against filings and other credible primary material. Do not rely on a chatbot’s summary when you have not checked the cited document.
- Check whether the information is current and complete. Look for the date and source behind each material claim. If the chatbot cannot establish access to relevant current or paywalled data, do not treat the resulting analysis as a full market view.
- Decide independently whether the risk fits. Consider how the investment would affect your portfolio and whether you could tolerate a loss. A chatbot’s analysis is not personalized risk management.
ChatGPT, market-data services, and automated advice are different tools
General-purpose chatbots, professional market-data services such as Bloomberg, and algorithmic or robo-advisory services are not interchangeable. They can differ in data freshness and access, how clearly sources can be verified, whether they only provide analysis or execute transactions, and who controls risk management. The reporting does not provide a current side-by-side evaluation or pricing for these options, so it does not support ranking them. Compare a service’s actual data coverage, transparency, costs, and role before relying on it.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is ChatGPT a crystal ball for stock prices?
No evidence in the reported portfolio example establishes that ChatGPT can reliably forecast stock prices or deliver repeatable outperformance. As Dan Moczulski, eToro’s UK managing director, put it in a statement quoted by Ars Technica from Reuters: “The risk comes when people treat generic models like ChatGPT or Gemini as crystal balls.” The practical distinction is straightforward: a chatbot may help you frame questions and review arguments, but its answer is not proof of future performance.
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