Technological revolutions don’t happen in a vacuum. They happen when economic pressure, technological possibility, and human psychology collide. That’s exactly what is happening with AI in 2025.
What looks like hype from the outside is actually a dense network of incentives, fears, and competitive pressures that make the current AI wave not just predictable — but inevitable.
To understand AI clearly, you must understand the economic forces accelerating it.
Every major shift in technology triggers a familiar pattern:
This pattern happened with:
And now: Artificial Intelligence.
The speed of the capital cycle.
Pre-AI startups needed years of product-building before attracting funding.
Today, a startup can raise millions with:
This accelerates the boom — but also the coming shakeout.
Capital is not irrational; it is impatient.
Money wants to capture the next trillion-dollar platform early, even if it means backing dozens of companies that won’t survive.
AI feels frenzied because capital behaves frenzied during pivotal technological shifts.
In the early 1900s, nations realized industrial power depended on energy.
Today, companies realize competitive advantage depends on compute.
This is why NVIDIA, TSMC, Broadcom, and ASML became some of the most valuable companies in the world nearly overnight.
They are the new oil companies, powering the entire AI economy.
Just as industrialization depended on:
AI depends on:
Companies aren’t investing in AI because it’s fashionable.
They’re investing because compute availability will determine competitiveness.
AI isn’t just software.
It is an energy-hungry intelligence layer that demands new infrastructure.
A quiet but powerful force behind the AI frenzy is institutional fear.
Executives may not fully understand AI, but they understand statements like:
This fear is grounded in history:
No executive wants to repeat those mistakes.
So businesses adopt a simple rule:
“We may not understand AI fully, but we can’t afford to be the last to figure it out.”
This creates an environment where even uncertain AI investments feel necessary.
Hype is not irrational.
Hype is the shadow of possibility.
Companies willingly overspend in early stages of technological waves for five reasons:
A pilot AI project may cost $100K,
but missing the AI wave could cost billions.
Companies invest because competitors invest.
Boards demand AI strategies even when organizations aren’t ready.
Vendors promise “AI-powered everything,” forcing buyers to respond.
Early movers in the internet, mobile, and cloud gained lasting structural advantages.
Overinvestment is not an error — it’s insurance.
It’s easier to cut AI budgets later than to rebuild market share lost to proactive competitors.
The heart of the AI frenzy is not technology —
it is economics.
For the first time in decades, productivity growth in developed economies has slowed.
Executives ask the same question:
“How do we get more output without hiring more people?”
AI is the first technology since the internet that promises multiplicative productivity, not merely additive.
The math is simple:
If a team of 100 can perform like a team of 150
without hiring 50 more people,
that is a structural advantage.
AI isn’t replacing workers — it’s replacing tasks within jobs.
This distinction fuels the economic incentive behind the AI frenzy.
People often compare the AI wave to the dot-com bubble.
That’s true, but incomplete.
2025 feels like two timelines merged:
AI combines both:
The hype of 1999 + the infrastructure shift of 2010.
This is why AI feels contradictory:
It’s not one era repeating —
it’s two eras colliding.
The economic forces driving AI are not random.
They are the same forces that drove every major technological transformation:
Understanding these forces helps you see AI not as a passing fad, but as a predictable economic transition — messy, loud, and full of both opportunity and risk.
In the next chapter, we’ll explore why most AI startups will fail, not because the technology is weak, but because the economics of AI create a brutally competitive landscape.
The winners will be few.
The losers will be many.
And the reasons are structural, not emotional.
Chapter 1 — Why AI Feels Both Magical and Overhyped
Understanding the dual nature of AI's breakthroughs and limitations in 2025.
Chapter 3 — The Reality, Most AI Startups Will Fail
Why the majority of AI startups are structurally set up to fail, not because of hype, but because of economics, competition, and dependency risks.