AI Investment Advice Boosts Confidence — But Risks Costly Mistakes

The Role of Human Judgment in the Age of AI

Artificial intelligence has become a powerful tool in the investment world, but it also highlights the critical importance of human financial advisers. In many situations, the best decision is to do nothing, yet AI systems often push investors toward action. A skilled financial adviser can help counter this tendency and guide clients toward more thoughtful decisions.

Why AI Encourages Action Over Inaction

There are several key reasons why AI in the investment space can lead to an overemphasis on action:

1. Action Bias in Human Nature: Psychologists refer to this as “action bias,” where people tend to favor taking action even when inaction might be more beneficial. This natural inclination makes investors less likely to turn to AI when they believe doing nothing is the right choice.

2. AI Replicates Human Biases: Large language models (LLMs) are trained on data that reflects human behavior, which means they often replicate the same biases. As Philip Resnik, a professor at the University of Maryland, wrote in the September 2025 issue of the journal “Computational Linguistics”:

   “Harmful biases are thoroughly baked into what LLMs are. There is no bug to be fixed here. The problem cannot be avoided in large language models as they are currently conceived, precisely because they are large language models.”

3. AI Tends to Agree with Users: AI models often provide advice that aligns with user preferences, sometimes to an excessive degree. For example, if an investor asks whether they should sell their stocks due to a geopolitical event, the AI may suggest selling—even if it’s not the best move. This tendency was confirmed by a study published in the journal “Science.” The research found that leading LLMs were 50% more sycophantic than humans, offering advice that was flattering and people-pleasing. Myra Cheng, the study’s lead author, noted that “by default, AI advice does not tell people that they’re wrong.”

The Loser’s Game of Investing

The danger of AI-driven action bias becomes clearer when considering that investing isn’t always a winner’s game. In many cases, doing nothing is the most effective strategy. This idea was popularized by Charles Ellis in his 1985 book Winning the Loser’s Game.

Ellis compared investing to tennis, distinguishing between winner’s games and loser’s games. In a winner’s game, success comes from making better moves. In a loser’s game, victory is achieved by avoiding mistakes. For amateur tennis players, the goal is to keep the ball in play until the opponent makes an error.

Ellis argued that investing is similar: success comes from minimizing unforced errors rather than chasing high-risk opportunities. He suggested that the best strategy for most investors is to buy and hold a broad market index fund, which mirrors the concept of lobbing the ball back in tennis—keeping things simple and steady.

The Value of a Financial Adviser

In this context, the role of a financial adviser becomes even more crucial. While AI can provide insights and recommendations, it lacks the nuanced understanding of human psychology and the ability to challenge clients’ assumptions. A good adviser can help investors recognize when inaction is the wisest course of action, countering the natural tendency to act impulsively.

Mark Hulbert is a regular contributor to CryptoLiveDaily. His Hulbert Ratings tracks investment newsletters that pay a flat fee to be audited. He can be reached at mark@hulbertratings.com.

Additional Resources

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• Here’s the next AI ‘battleground’ — and how investors can get in on the action