The “Both-Sides” Trap: Why Contradictory AI Fears are Crushing Tech
From ROI skepticism to disruption alarms, explore why the market doesn’t need a consistent narrative to trigger a massive selloff.
Critics claim the AI market is behaving irrationally by fearing both a lack of ROI and a total industry disruption simultaneously. However, using the “Horse and Buggy” heuristic and classic financial literature on divergence of opinion, this article argues that contradictory fears don’t cancel out—they compound. We examine why the current tech selloff is a textbook example of a market driven by heterogeneous agents, where the battle between different bearish mandates creates a downward pressure that logic alone cannot explain.
Financial commentators on TV have been quick to point out a logical inconsistency in the current AI market narrative. They argue that critics are talking out of both sides of their mouths:
The ROI Skeptics: “AI is a bubble; the infrastructure spend is massive, but the returns for clients aren’t showing up.”
The Disruption Alarmists: “AI is too successful; it’s going to automate software incumbents into obsolescence.”
The AI defenders argue both fears cannot be true. If AI doesn’t work (No ROI), it can’t disrupt incumbents. If it disrupts incumbents, it clearly works (High ROI).
However, the market is not a single person with one opinion. It is a collection of thousands of portfolio managers, each with different mandates. The finance literature and some prior examples supports the contention that two seemingly inconsistent views can drive stock price and investment decision.
There is no inconsistency in Group A selling Nvidia because they fear a capex bubble, while Group B sells Salesforce because they fear Agentic AI will replace seat-based licenses. When both groups act on their specific fears, the entire sector moves down.
The “horse and buggy” analogy (historically attributed to a leading banker at Michigan Savings Bank in 1903 who advised Henry Ford’s lawyer not to invest) provides the perfect heuristic.
Imagine it’s 1905:
Investor A refuses to invest in Ford because the infrastructure (paved roads/gas stations) is too expensive and the ROI is decades away.
Investor B sells their shares in Carriage-Maker Inc. because they fear the “horseless carriage” will make the current business model obsolete.
Both have a bearish view, but for opposite reasons. Their combined selling pressure creates a market-wide fear of the auto-sector, even though their reasons are technically contradictory.
What the Literature Says
This phenomenon is well-documented in finance literature: Edward Miller, in a paper published in the Journal of Finance, in 1977 argues that when uncertainty is high, divergence of opinion leads to massive volatility. Prices don’t reflect an average view; they reflect the battle between the most optimistic and most pessimistic agents.
Brock & Hommes (1998) in their work on Heterogeneous Agent Models (HAM) proves that a market full of bounded rational agents—some following fundamentals (ROI), others following trends or disruption narratives—create nonlinear price shifts that a rational observer would find inconsistent.
Yan Gao, Connie X. Mao, and Rui Zhong (2006) in their study, “Divergence of Opinion and Long-Term Performance of IPOs,” use Miller’s framework to explain why high-uncertainty often leads to volatile price corrections in IPO markets.
The bottom line is that contradictory fears don’t cancel out they can lead to additional selling by each group. In the current situation, it appears as though AI technology is a “bust” for the people building it and a “threat” to the people competing with it leading to the current tech selloff.
Authors Note: This multi-topic blog has articles on economic policy, (health care, student debt, taxes, and Social Security), politics (very closely following the contest for the House of Representatives), personal finance (both issues affecting people entering the workforce and people entering retirement) and today investments and markets. Most of the material on the blog is free and I am committed to keeping it that way but some material (usually only a portion of an article) is available exclusively for paid subscribers.
This post on the impact of the wide divergence of opinions on AI on the current tech market is free to all.
People who liked this blog may also want to read A Statistically Well Behaved Transformation of PE for Growth Value Inference.
I appreciate your readership and support.