I believe the AI and crypto gold rush is colliding with a basic problem: we do not have enough cheap, reliable power to run the future everyone is buying into.

I want to walk you through a simple idea that most people are missing while they cheer for fancy software and crazy market caps: digital tech needs real world power and land, and those two are not free or unlimited. If you are invested in tech, crypto, real estate, or simply want to understand where risk actually lives in this boom, keep reading. I am going to break this down clearly, give plain talk on the numbers, point out a few historical lessons, and offer practical steps for how to think about investments through this lens.

Companies are promising an AI-driven future. They talk about tools that will change how businesses run, how consumers live, and how money moves. Crypto believers say digital money will reshape finance. Investors have poured huge sums into both ideas.

When lots of money chases a belief, prices go up. That is normal. But two things make today special:

Both put extra stress on electricity systems and land near grid and water resources. That stress has real costs for households, businesses, and governments.

A tiny group of companies is carrying a massive share of the market and expectations. That creates a fragile system: if one big link breaks, the chain could snap.

I like to use single examples to show a bigger problem. Nvidia is not just another chip company—today it plays an outsized role:

Big numbers to grab your attention.

When a single firm represents a big part of the market, that market becomes dependent on that firm’s ability to deliver revenue and profit. If something interrupts the supply chain, demand, or the firm’s growth, the market can swing violently. That is a major source of systemic risk.

Researchers and industry reports estimate trillions of dollars in data centre spending over the next decade. That sounds abstract, so let me put it plainly:

Why capital intensity can lead to a bubble:

When companies spend massive amounts hoping for future returns that are not guaranteed, we see two things:

Analyses of wholesale electricity prices across many regions show something not very surprising: places near heavy data centre activity have seen big price rises over recent years. In some areas electricity costs have more than doubled compared to five years ago.

Higher wholesale prices trickle down to households and businesses. The grids that serve cities and towns are interconnected. When a data centre draws power, it affects the whole region. That means your utility bill, rents, and local business costs can rise because a big tech load moved in nearby.

Big tech and cloud players are trying to secure power by:

There is also growing interest in small modular reactors (SMRs) from big tech names because they offer steady, dispatchable power. But a reality check matters:

On the other side, renewables are cheaper per megawatt in many places. But they are not consistent and reliable. AI data centres and crypto miners require steady power. That means renewables alone cannot be the whole solution unless matched with very large storage or dispatchable backup—both of which are expensive and slow to scale.

Bitcoin miners run 24/7 until the hardware is no longer profitable. That constant demand is a poor match for variable renewable sources. Mining puts baseline demand pressure on grids and can push up prices in the same way large data centres do.

If bitcoin were a country, its electricity consumption would rival medium sized nations. Most of the electricity powering mining today comes from fossil fuels.

Estimates of global data centre capex required to meet AI demand by 2030 run into the trillions.

To put this into perspective:

In many countries, progress on building high-voltage transmission lines has fallen behind needs. Millions of kilometers of power lines—approximately 80 million kilometers—must be built or refurbished globally by 2040 to meet energy goals.

Also, according to Rinnovabili, while global investment in power transmission rose by 10% in 2023 to reach $140 billion, it must exceed $200 billion annually by the mid-2030s just to meet rising demand. To reach full national and global emissions goals, that figure needs to climb to between $250 billion and $300 billion.

But unlocking these investments is not just a matter of financial commitment. Significant structural obstacles must also be overcome. New grid infrastructure typically takes between 5 to 15 years to plan, permit, and complete. In the United States, multi-state transmission lines often take a decade or more to progress from proposal to final permitting.

All of the above makes it much harder for AI to have enough power at a sustainable cost in the short amount of time that people have high expectations for. Just like other cycles in the past, we are at a phase where people’s expectations exceed reality.

We have seen bubbles just like this before.

History gives us pattern recognition. Past tech bubbles followed a familiar rhythm:

In the late 1990s, massive investment into internet infrastructure and companies pushed valuations into the stratosphere. When real profits failed to match expectations, markets corrected violently. Today, the concentration and the scale of capex remind me of that cycle.

In the 1800s, railways drew massive investment in land and infrastructure of around 6% (similar to where we are now) and then collapsed for many. Extreme capex relative to returns can produce catastrophic failures. The current AI-capex story has echoes of that era.

This brings me back to the 18 year real estate cycle I always mention. For those who don’t know, there is a long-run cyclical pattern in land and property markets, A roughly 18 to 19 year rhythm shows phases of expansion, peak, decline, and recovery.

This cycle has accurately predicted every bull and bear market in the last 200 years like 1929, 1989, 1999, 2008 and 2020. And right now we are just at the edge of the Winner’s Curse phase, the last phase before the peak.

When big technology-driven investment hits at the later stages of a real estate cycle, the fallout from a tech bust can amplify property valuation declines and credit stresses. If land values are near their cycle highs while tech capex runs hot, the combined shock could be deeper and more widespread.

A gradual scaling of grid upgrades, paired with increased storage and a slow rollout of small modular reactors, eases power constraints. Data centres and miners find ways to smooth demand, and markets absorb the capex. Growth slows but stays positive.

Then we would see grid constraints, higher wholesale power prices, and lack of transmission upgrades which cause margins to collapse for big artificial intelligence operations and miners. Investors reprice the sector heavily. Tech indices fall, property markets near data-hub areas weaken, and credit stresses rise. Of course, all of these are just my speculations and high probability guesses.

Trigger events to watch

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