AI Bubble 2025: Why "Doubling Down" is Leadership Psychology, Not Strategy
- Tony Grayson
- 3 days ago
- 7 min read
Updated: 1 day ago
By Tony Grayson Tech Executive (ex-SVP Oracle, AWS, Meta) & Former Nuclear Submarine Commander
The biggest argument against a bubble is that "everyone is doubling down." History and psychology tell us that is exactly when we should be most worried.
Where I Land: Having spent years commanding nuclear submarines and later building cloud infrastructure for global tech giants, I’ve learned that the most dangerous variable in any complex system isn't the hardware…it's the human operator. I don’t think the current technology wave is a fad; the innovation is real. But I do think the behavior surrounding it has decoupled from reality. We’re mistaking biological impulses for strategic conviction.
Whenever the word "bubble" enters the financial lexicon, a fierce counter-narrative immediately emerges. As we face the AI Bubble 2025 debate, the defense is always the same:
"How can this be a bubble? Look at the CAPEX spending. The smartest people in the room, the biggest institutions, and the most successful CEOs are doubling down. Investors can’t get enough. Demand is real, so the valuations must be rational."
This argument sounds convincing because it relies on "social proof." If everyone is doing it, it must be right. Even tech titans like Mark Cuban and Google's Sundar Pichai have recently voiced concerns about "irrationality" in the market, yet the spending continues.
But this defense mistakes volume for value. The fact that "everyone is doubling down" doesn't prove we aren't in a bubble. Ironically, it is often the definitive psychological signal that we are.
When we see massive, synchronized investment waves, we’re usually not seeing collective wisdom. We’re seeing collective wiring. We like to believe spreadsheets and rational actors drive markets; in reality, they are often driven by dopamine, cortisol, and ancient evolutionary impulses.
Here is the leadership psychology data behind why "doubling down" is often a symptom of behavioral bias rather than strategic brilliance.
1. The Evolutionary Imperative: Herd Mentality
The most powerful force in finance isn't interest rates; it's the deep-seated human need to belong to the group.
In evolutionary terms, being separated from the herd usually meant death. Our brains have evolved to feel safer when we are mimicking the actions of those around us. In modern finance, this translates to "Career Risk." It is professionally safer for a fund manager or a CEO to lose money doing what everyone else is doing than to risk missing out on gains by standing alone.
Psychologists call this "informational conformity." When a situation is ambiguous, we rely on others' actions as a proxy for truth.
The Evidence: The classic demonstration of this is the Asch Conformity Experiments of the 1950s. Subjects were shown a line and asked to match it to one of three comparison lines. The answer was obvious. However, when surrounded by actors who intentionally chose the wrong line, nearly 75% of participants conformed at least once, denying their own senses to fit in with the group.
When today's investors see billions pouring into a specific sector, they aren't calculating fundamentals; they are looking at the lines on the wall and agreeing with the group, terrified of being the outlier.
2. The Neurochemistry of FOMO and Greed
We often dismiss "Fear of Missing Out" (FOMO) and greed as simple character flaws. They are not. They are powerful neurochemical responses.
When we see others succeeding, like watching competitors' stock prices soar or reading headlines about massive funding rounds, our brains react intensely. The fear of missing out on status or resources triggers the amygdala, the brain's fear center, creating genuine anxiety.
Conversely, the prospect of quick gains triggers the brain's reward system, flooding it with dopamine. Neuroeconomics research has shown that the anticipation of financial gain activates the same neural pathways as cocaine.
The Evidence: A study published in Neuron found that the brain’s reward prospects (greed) can effectively suppress the brain’s risk signals. When the potential for a massive upside is presented, our biological capacity to assess downside risk is chemically dampened. When "everyone is doubling down," the dopamine rush encourages us to ignore the cliff edge.
3. The Cognitive Trap: Recency Bias and Linear Thinking
A primary driver of bubble psychology is the "belief that past performance equals future performance." In behavioral economics, this is known as the representativeness heuristic or, more simply, Recency Bias.
Humans are terrible at intuitive statistics. We look at the immediate past (the last 12 to 24 months of explosive growth), and we instinctively extrapolate that line straight up and to the right forever. We assume the near future will look exactly like the recent past.
The Evidence (Historical Data): History proves that growth is almost always an S-curve…it explodes, then flattens. Bubbles occur when investors price an S-curve as if it were a straight exponential line.
The Analog: Forget the Dot-Com bubble; look at the Nuclear Construction Boom of the 1970s. Utilities assumed post-war electricity demand would double every decade and projected it linearly forever. They borrowed billions to build massive fleets of reactors, most famously the Washington Public Power Supply System (WPPSS).
The thesis was sound: "The world needs more energy." But the behavior was flawed. The demand curve was an S-curve, not a straight line. When efficiency improved and demand flattened in the 1980s, the "Whoops" project collapsed into the largest municipal bond default in history. They built cooling towers for energy that nobody bought.
Today, we are pouring concrete for gigawatt-scale AI clusters based on the exact same linear extrapolation. We are building the WPPSS of the 21st century, confusing a temporary spike in training demand for infinite utility.
4. Action Bias: The "Penalty Kick" Syndrome
If there is one thing corporate leadership despises, it is inaction. We are wired to believe that doing something is always better than doing nothing. In psychology, this is known as Action Bias.
This is best illustrated by the Goalkeeper's Dilemma. This statistical analysis of professional soccer penalty kicks shows that goalkeepers save the most goals by staying in the center of the net. Yet, in practice, keepers dive left or right 94% of the time. Why? Because diving and missing looks like "effort." Standing still and missing looks like "incompetence."
In the current AI market cycle, capital expenditure is the corporate equivalent of diving. A CEO who spends $5 billion on GPUs and fails can say, "We swung for the fences and missed." A CEO who sits on the sidelines and misses the wave gets fired for lack of vision. The biological driver is the same: it feels safer to be seen "doing something" than to stand still and be judged.
5. Authority Bias: The Media Galvanizers
Finally, we have an innate trust in people who "galvanize us in media." This is known as authority bias. We tend to attribute accuracy to confidence.
When charismatic CEOs or celebrated VCs appear in the media with absolute certainty about a "new paradigm," our critical thinking defenses lower. We assume that because they are rich and famous, they must possess secret knowledge. We forget they’re subject to the same herd mentality and dopamine loops as the rest of us, just with more zeros attached.
Evidence: University of Pennsylvania professor Philip Tetlock conducted a 20-year study on expert predictions. His conclusion? The average expert was roughly as accurate as a dart-throwing chimpanzee. Crucially, Tetlock found that fame is an imperfect proxy for truth. The more often an expert appears on TV, the more likely they are to be wrong.
The Sober Playbook: Leading Against Your Own Biology
If you are a leader, the answer isn't to become cynical. It is to recognize your own biology and build systems to counter it.
Define Your Own Signal: Stop looking at your competitors' CAPEX as a proxy for truth. If you can’t make the math work on your own P&L, don’t assume they know something you don’t. They are likely just looking at you.
Stress-Test the S-Curve: Ask your team: "If adoption flattens next year, does this investment still make sense?" If the answer is no, you are gambling on a straight line in a curved world. (See my article on why business continuity plans fail for more on stress-testing assumptions.)
Create Safety for Dissent (Break the Abilene Paradox): Management expert Jerry Harvey described the "Abilene Paradox," where a group collectively agrees to a decision that no single individual actually wants, because they incorrectly assume everyone else wants it. Bubbles are fueled by this "Pluralistic Ignorance." Assign a "designated dissenter" in every meeting to break the illusion of unanimity.
Separate Technology from Psychology: You can be bullish on the tech and bearish on the behavior. They are not mutually exclusive.
The Sober Second Thought
To say we might be in a bubble is not a Luddite rejection of new technology. The underlying innovations driving the current boom are likely real and transformative.
But we must learn to separate technological reality from behavioral insanity.
When the primary argument for continued investment is the sheer volume of investment already occurring, it is time to worry. That isn't the sound of rational analysis. That is the thundering sound of a herd, driven by biology, running full speed in one direction.
Related Reading:
This video provides an excellent analytical framework for evaluating the current market hype, complementing the psychological perspective discussed above.
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Tony Grayson is a recognized Top 10 Data Center Influencer, a successful entrepreneur, and the President & General Manager of Northstar Enterprise + Defense.
A former U.S. Navy Submarine Commander and recipient of the prestigious VADM Stockdale Award, Tony is a leading authority on the convergence of nuclear energy, AI infrastructure, and national defense. His career is defined by building at scale: he led global infrastructure strategy as a Senior Vice President for AWS, Meta, and Oracle before founding and selling a top-10 modular data center company.
Today, he leads strategy and execution for critical defense programs and AI infrastructure, building AI factories and cloud regions that survive contact with reality.
Read more at: tonygraysonvet.com
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