Here’s what’s on our plate today:

• 🧠 AI stock picks go mainstream—but retail investors risk more than they know.

• 📲 ChatGPT’s new wake-up call, Threads feed controls, Meta’s kid safety failure.

• 🗳️ Poll: Would you trust a chatbot to pick your stocks?

• 💡 AI chatbots ≠ Bloomberg terminals—verify everything.

Let’s dive in. No floaties needed…

The Laboratory

The promise and perils of AI in retail investing

When Leonardo DiCaprio played the character of Jordan Belfort in The Wolf of Wall Street, he might not have realized that his portrayal of the former stockbroker and trader would inspire many to take a closer look at people working on Wall Street. Despite being treated as a villainous backdrop or at least as a morally compromised arena, Wall Street pulls in millions of people who dream of making money through financial institutions. However, even beyond Wall Street, with the internet and online apps making investing in the financial markets easier, investment brokerage accounts have increased notably in recent years.

In the U.S., the percentage of households with stock holdings increased to an all-time high of 58% in 2022, according to the Federal Reserve’s Survey of Consumer Finances, up from 49% in 2013. And it is expected to grow, thanks in part to the emergence of AI tools. Users are increasingly turning to AI chatbots to help guide them through the process of investing, even going to the extent of asking chatbots to pick the stocks they should invest in.

According to a Reuters report, at least one in 10 retail investors is using a chatbot to pick stocks. This may sound like a viable option since AI tools can analyze massive amounts of online content to indicate which stocks show the most promise. Relying on them for stock investment is riskier than many appreciate. However, despite the risks, the robo-advisory market is poised to accelerate.

How AI is driving the next wave of retail investing

The robo-advisory sector covers fintech firms, banks, and wealth managers offering algorithm-driven financial advice. This market is expected to generate $470.91 billion in revenue by 2029, up from $61.75 billion in 2024, a surge of nearly 600%, according to Research and Markets.

The increasing growth of AI in investment markets is based on AI’s ability to analyze vast amounts of data, such as market trends, historical price movements, and economic indicators, to identify patterns and make trading decisions. The use of AI tools has allowed some of the stock market traders to automate their strategies, further allowing them to take advantage of market opportunities.

Beyond the stock market, AI is used by retail investors, who make up around 20% of the U.S. stock market and over 60% indirectly through individual retirement accounts, according to Barclays Plc.

According to a Bloomberg report, while retail investors are known for their loyalty to a handful of companies and meme stocks, like GameStop Corp, the advent of AI-driven platforms’ ability to let users scan thousands of stocks and respond to real-time data as fast as sophisticated hedge funds has led to a shift in their investment patterns.

However, it is not just AI chatbots that investors are looking to for advice.

Trading apps race to add AI features

Not wanting to be left behind, many online investment apps started integrating AI capabilities into their platforms.

Platforms like Robinhood have introduced AI tools that analyze factors influencing stock prices and streamlining trading. These tools are touted as capable of formulating complex strategies for investments like options by helping clients identify trades suited to their risk profiles.

Similarly, Interactive Brokers Group Inc. offers access to Reflexivity, a third-party platform that tracks diverse data and provides portfolio-specific insights. For example, traders can receive alerts on how changes in the yield curve may affect different stock groups. Such technologies significantly broaden traders’ exposure to equities.

However, while these reflect a structured way of using AI, many others have chosen a very different path.

The unregulated rush into AI-powered trading

The cost of gathering data that allows investors to assess the risks before investing is both time-consuming and expensive to access. Retail investors are side-stepping the expensive information terminals in favor of chatbots. Users are relying on them to scan sectors, generate watchlists, or find small sets of names meeting specific fundamental filters (low debt, rising margins, moat, etc.). This is often how investors ‘bootstrap’ research without expensive data terminals.

Users are also reportedly using chatbots to request summaries of earnings, explanations of financial ratios, or plain-English write-ups of SEC filings. Chatbots are used to translate filings or technical commentary into actionable bullets.

Additionally, Chatbots summarize newsflow, social sentiment, earnings call tone, product reviews, or forum chatter (Reddit/Twitter). Users ask for distilled sentiment trends or flagging events that might affect a ticker. Institutions do this at scale; retail users do it ad hoc.

The allure of AI chatbots for retail investors, however, comes with its own set of risks.

Hallucinations, scams, and privacy risks in AI investing

LLMs can invent numbers, misquote dates, or misinterpret filings. Media reports highlight the risk posed by users relying on outputs without verification. Additionally, public LLMs don’t have live market feeds or paywalled research; they may miss the most recent filing or a proprietary datapoint.

Additionally, models trained on historical text can suggest strategies that worked in-sample but fail out-of-sample. Backtests from naive screens are often misleading. Academic and industry reviews of robo-advisor/AI strategies warn against this.

Then there is the risk of fraudsters using AI to create fake endorsements, deepfake voices, or automated pitch decks to run pump-and-dump scams. Regulators have warned about AI-enabled investment fraud. The SEC has issued alerts on AI and investment fraud.

AI chatbots are unreliable when it comes to data privacy. Even CEOs of major AI companies, including OpenAI, have issued public statements about the lack of confidentiality of AI chatbots. Users who paste portfolio holdings, account statements, or proprietary research into third-party chatbots also risk exposing sensitive data.

Why human oversight is still needed

AI chatbots are accelerating retail adoption of automated investing workflows; they democratize access but do not remove the need for verified data, risk controls, and human judgment.

While retail investors look to use AI chatbots to streamline their investment strategies, they should not forget that the biggest advantage will remain with institutions that combine proprietary data, engineered LLM pipelines, and compliance. Another important lesson: navigating difficult situations in the stock market takes time and experience, and AI models cannot replace that.

At the end of the day, retail investors should remember that AI may be the newest player on Wall Street, but it is not a miracle worker. For every investor who sees opportunity in chatbot-powered stock picks, there are cautionary tales of hallucinated numbers, misleading signals, and misplaced trust.

What AI does offer is accessibility: the ability for retail investors to sift through information, generate ideas, and test strategies without a Bloomberg terminal or costly research subscription. But the technology cannot replace hard-earned judgment, risk management, or the discipline that underpins long-term success in financial markets. The firms that will benefit most are not individual traders chasing the next meme stock, but institutions building AI into systems fortified with proprietary data and compliance checks.

Retail investors must learn to see AI for what it is: a useful tool, not a substitute for due diligence. Wall Street has always thrived on ambition, but AI should sharpen it, not blind it.

Roko’s Pro Tip

Monday Poll

Bite-Sized Brains

• ChatGPT wants to be your morning coffee: OpenAI launches Pulse, a new AI briefing tool designed to kickstart your day—straight from ChatGPT.

• Threads gives you the remote: A new feature will let users tag posts to influence the algorithm and customize what shows up in their feed.

• Meta under fire for child safety gaps: Instagram is failing to protect minors despite having tools to do so, says UK’s online safety watchdog.

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