The Biggest AI Investing Mistake Is Happening Right Now

I ran across an interesting article, and I think a lot of people will walk away from it with the wrong takeaway.

The piece focuses on new AI tools being rolled out by Anthropic. These systems can draft pitch decks, review financial statements, and integrate directly with platforms like Excel and Outlook. They are being positioned as tools for professionals across banking, asset management, and financial technology.

The market reaction was immediate. Shares of FactSet, Morningstar, S&P Global, and Moody’s all came under pressure as investors began to price in what this could mean for traditional research and data providers.

That part is straightforward. The tools are improving, and they will continue to take over repetitive, structured tasks.

But the most important point in the article is not what Anthropic’s technology can do. It’s what is slowing it down.

Anthropic’s leadership made it clear that adoption is not being held back by the models’ capabilities, but by how that capability spreads through real businesses. At the same time, Jamie Dimon acknowledged that even with increased investment and better tools, identifying winners and losers will remain difficult.

AI can process information. It can organize it, summarize it, and present it cleanly. What it cannot do is determine when that information changes behavior in a way that creates opportunity.

Markets do not move because information exists. They move when participants react to that information, often unevenly and, more often, late.

When tools improve, the assumption is that decision making becomes easier. In reality, information becomes more accessible, reactions become faster, and the difference between acting early and acting late becomes more important.

That’s not solved with more data. It’s solved with a defined process.

That’s where my approach is different.

As I often say, I am not trying to interpret every data point or react to every development. The focus is on identifying when fear has expanded and when it begins to fade. That shift is what creates opportunity— whether that means selling puts at elevated premiums or identifying stock trades as volatility begins to contract.

The indicator measures that transition directly.

  It does not rely on narratives, forecasts, or headlines.

  It tracks behavior.

  That process can be applied across both options and stocks because the underlying principle is the same. Fear expands, behavior becomes emotional, and opportunity begins to emerge as pressure starts to fade.

AI can assist with analysis. It can help surface information and even explain it. But it does not remove the need for a structured way to act on that information, especially in environments where reactions are inconsistent and timing matters.

If anything, faster access to information makes discipline more important.

The takeaway from the article is not that tools replace decision making. It is that information is becoming easier to access, which places more weight on how it is used.

That is exactly why we have the ITV indicator. It tells us when to act.