AI’s Dirty Secret: Fossil Fuels, Hidden Debt, and Old-School Capitalism

Data centers powering AI are resorting to fossil fuels due to grid connection delays, contributing to environmental degradation.

March 10, 2026 by Enrique Danes Leave a comment

We’ve been hearing the same mantra for years now: AI will change everything. And yes, some things will change. But what hasn’t changed, and it’s the really interesting, old-school political economy that sustains AI: the way its infrastructure is being built, how it’s being paid for, and the perverse incentives to make it all happen.

Because when an industry requires obscene amounts of electricity and capital to grow, what we see is not the future, but the same old story of financial engineering, environmental factors and a geopolitical regulatory freebie.

Let’s start with the power source. Financial Times has published such shocking news Facing several years of delays in connecting to the grid, some data centers are adapting aircraft engines, as well as using diesel and gas generators.. Yes, you read that right: the future is being built by burning massive amounts of fossil fuels. And, of course, under the pretext of urgency and competition, there is pressure to “relax” restrictions on the use of these generators. AI is being sold as innovation, but behind the scenes grids are overloaded, local communities are paying the price and our climate continues to deteriorate.

At the same time, and as usually happens when capex skyrockets, no one wants to talk about debt. Major players in the Big Tech and AI ecosystem Data financing with more than $120 billion off their balance sheets through special purpose vehicles financed by Wall Street and private credit markets.. This isn’t an accounting technicality: it’s a real-time bubble alert. When an industry needs to keep growing to justify its narrative and at the same time needs financial ratios to look “healthy”, it shifts the problem elsewhere. And risk does not disappear: it is redistributed where transparency is low.

Then there is the geopolitics of control. While we in the West are still mired in lobbying and techno-optimism, China has just released draft rules to tighten oversight of artificial intelligence services designed Emulates human personality and engages users in emotional interactions.

We can (and should) discuss the Chinese model of freedom and censorship frameworks, but at least Beijing is acknowledging that these systems can create psychological dependence. On the contrary, we are still treating it as some minor side problem that the market can magically self-regulate.

What emerges is a classic portrait of infrastructure capitalism and A get-rich-quick route for some: Rapid growth driven by wild expectations, financed with increasingly less transparent mechanisms and sustained by energy solutions that confront a climate emergency that some claim “no longer exists”. The investment frenzy in data centers and AI is sweeping India With multi-billion dollar commitments to water, energy, subsidies and jobs concerns.

Meanwhile, Alphabet bought data center power specialist Intersect for $4.75 billion To secure power supply for its expansion in AI. The message is the same: AI is no longer an app, it’s an industrial infrastructure hungry for power, land, water and finance. Let’s think about the efficiency of the Chinese.

I recently wrote about The Trump administration’s decision has crippled offshore wind in the US On the absurd “national security” pretext. In reality, few things better illustrate contemporary strategic folly: on the one hand, it is about narratives of technological dominance and leadership in AI, on the other, scalable sources of power are destroyed when they are most needed. It’s the same old asymmetry, but magnified: We want data centers everywhere, but we don’t want to plan for a big grid, renewables or storage. We want to “win” the technological race, but not accept the industrial discipline that demands this. We seek innovation without cost or limit assumptions.

The concern here is the logic driving investment. When the dominant discourse is “build it and we’ll worry about the consequences later”, the result is usually a combination of overcapacity, externalities and secret bailouts. After all, you end up with underutilized infrastructure and misallocated debt. At worst, with a strained energy system, local communities foot the bill and an industry that, when it stops growing at the promised rate, will leave a trail of financial risk packaged in junk products.

In conclusion: AI has valuable uses and is here to stay. But if we really want to separate the wheat from the chaff, we have to ask the hard questions: How much energy does it consume and where does it come from? What financial incentives maintain it and what are the risks? Are there rules to protect users and society when models are designed to maximize usage time and reliability? The irony is that if AI is going to change our world, we must build it on sustainable foundations. Financing off balance sheets and feeding it with jet turbines is not the future. It’s a little more than steampunk.

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This post was Previously published Enrique Danes‘Blog.

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