AI in Investing: 13% of Retail Traders Ride the Algorithmic Wave

The Algorithmic Investor: One in Eight Retail Traders Depend on AI for Stock Picks as Market Sees 600% Growth

A large segment of the worldwide retail investing community is now relying on Artificial Intelligence (AI) - particularly large language models like ChatGPT - with their financial decisions, spurring both unprecedented market expansion and expert caution. A recent global survey by brokerage firm eToro, encompassing 11,000 retail investors, shows that approximately half would consider AI tools for financial advice, with a striking 13% already buying stocks based on AI recommendations. This trend highlights a rapidly evolving landscape where algorithms increasingly influence individual portfolios, even as financial professionals warn against uncritical adoption.

The burgeoning market for AI investment advisors is projected to explode, with analysts from Research and Markets forecasting a 600% expansion by 2029. This surge is driven, in part, by the democratization of AI capabilities and a rising need for agility in navigating increasingly volatile business environments. The "AI in Financial Planning and Analysis (FP&A)" market alone is expected to grow by USD 48.86 billion between 2024 and 2029, a compound annual growth rate (CAGR) of 26.9%. Key drivers cited include the emergence of generative AI, conversational analytics, and a broader shift towards prescriptive and autonomous finance models.

Expert Discretion Advised Amid Generative AI Enthusiasm

Despite the clear enthusiasm among retail investors, financial experts call for caution. Dan Moczulski, managing director at eToro in the UK, stated a prevailing concern: "General AI models can misquote figures and dates, lean too hard on a pre-established narrative, and overly rely on past price action to attempt to predict the future." Moczulski and others advise that investors prioritize AI platforms specifically engineered and trained to analyze financial markets, rather than multipurpose conversational agents.

Jeremy Leung, a former analyst with UBS, illustrates the nuanced approach some sophisticated users are adopting. After leaving the Swiss bank, Leung uses ChatGPT to analyze stocks for his multi-asset portfolio. Without access to expensive institutional data services like Bloomberg terminals, Leung finds that "even a basic ChatGPT tool can do a lot and replicate a lot of the workflows that I used to do." However, he also recognizes inherent limitations, noting that AI tools often cannot access information behind paywalls and require carefully crafted prompts-such as "assume you're a short analyst, what is the short thesis for this stock?" or "use only credible sources, such as SEC filings"-to yield reliable results.

Performance Metrics and Underlying Risks

The potential for AI to pinpoint lucrative investment opportunities is not just theoretical. In March 2023, the comparative finance company Finder assigned ChatGPT to select a basket of 38 stocks based on criteria such as low debt, sustained growth, and competitive advantages. This AI-curated portfolio, which included prominent names like Nvidia and Amazon alongside consumer staples such as Procter & Gamble and Walmart, subsequently rose nearly 55%. This performance exceeded the average of the UK's ten most popular funds, including offerings from Vanguard, Fidelity, and HSBC, by almost 19 percentage points.

Nevertheless, such compelling results do not erase the inherent risks. ChatGPT itself includes disclaimers advising against its use for professional financial advice, and OpenAI has not released data on the number of users relying on its chatbot for investment decisions. Moczulski cautions that while "AI models can be brilliant," the primary risk arises "when people treat generic models like ChatGPT or Gemini as crystal balls." There is concern that investors making profits during periods of market buoyancy-such as the current environment where the S&P 500 has gained 13% this year following a 23% surge last year, and the pan-European STOXX 600 is up almost 10%-may not develop the resilience or judgment to navigate market downturns. Leung underscores this, stating, "If people get comfortable investing using AI and they're making money, they may not be able to manage in a crisis or downturn."

The market for AI in financial planning and analysis is divided by type (rule-based, machine-learning-based, natural language processing), application (predictive forecasting, advanced analytics, risk management, automated reporting), deployment (cloud-based, on-premises), and geography. Key industry players in this evolving ecosystem include Alteryx Inc., Amazon Web Services Inc., Anaplan Inc., Google LLC, IBM Corp., Microsoft Corp., Oracle Corp., Palantir Technologies Inc., and SAP SE, among others. As these technologies mature and become more integrated into financial workflows, the distinction between general-purpose AI and specialized financial AI is likely to become a crucial factor for investors seeking to leverage these tools responsibly.