Using large models to assist investment! Research institutions: By 2029, the scale of AI investment advisory will grow by 600%
The AI investment advisory market size is expected to surge from USD 61.75 billion in 2023 to nearly USD 471 billion by 2029, an increase of over 600%. Currently, about 10% of retail investors have used chatbots for stock selection, and another half of retail investors are open to it. Experiments show that the portfolios selected by ChatGPT have a return rate as high as 55%, far exceeding that of professional funds. However, experts warn that AI models carry risks such as outdated data and incorrect information
From Wall Street analysts to ordinary retail investors, artificial intelligence is rapidly penetrating the investment field.
According to the latest forecast from research firm Research and Markets, the global robo-advisory market size is expected to soar from USD 61.75 billion in 2023 to nearly USD 471 billion by 2029, growing over 600% in six years. Behind this prediction is the growing interest from investors.
Data from brokerage eToro shows that about one in ten retail investors currently use chatbots to select stocks, while half of the respondents indicated they would consider trying it.
The appeal of AI investment lies not only in the concept. According to media outlet Finder, in an experiment conducted in 2023, the stock portfolio selected by ChatGPT, which included companies like Nvidia, Amazon, Procter & Gamble, and Walmart, achieved an astonishing 55% increase, far outperforming mainstream funds in the UK market.
Former UBS analyst Jeremy Leung also stated that he now uses ChatGPT to guide his investment portfolio, claiming that “even a simple ChatGPT tool can accomplish and replicate many of the workflows I used to do,” partially replacing the expensive Bloomberg terminal functions.
However, amid the optimism, industry experts are intensively issuing risk warnings. Dan Moczulski, head of eToro UK, emphasized, “The risk arises when people treat general models like ChatGPT or Gemini as crystal balls.” These models may “misquote data and dates, overly rely on existing narratives, and depend too much on past price trends,” making AI tools specifically designed for investment a safer choice.
Professionals have also pointed out the limitations of general AI models. Jeremy Leung warned that because chatbots “cannot access data behind paywalls,” they may miss critical analytical information.
He added that to achieve ideal results, users must provide very detailed instructions, such as “Assume you are a short-selling analyst; what is the short-selling logic for this stock?” or “Only use reliable sources like SEC filings.” He finally reminded that if investors become too complacent after easily making money with AI, they may struggle to respond effectively when a market crisis or downturn occurs
