The US economy has been undergoing a profound transformation in recent years. An extraordinary amount of the nation’s goods and services are produced by a small group of seven big tech companies – Google, Apple, Microsoft, Amazon, Nvidia, Meta/Facebook, and Tesla. Europe and Germany have been envious of America’s technology might, but they should be careful what they ask for.

In the first half of 2025, these seven companies accounted for nearly all economic growth in the United States, and projections estimate that trend will continue into 2026. Without Big Tech, growth would have slowed to just 0.1% annually. These companies now make up nearly one third of the total value of the US stock market. They have become so central to the overall economy that they determine employment trends and investment decisions. Their domination of the stock exchanges means that a significant portion of American wealth, including retirement accounts, is dependent on their performance. 

Tech expert Paul Kedrosky notes that these companies’ ever-bigger share of the pie are “eating the economy”, much like the railroad barons and monopolies did in the late 19th century. With such a narrow, tech-focused economic engine, it means America’s future growth will be highly dependent on the spending decisions of these handful of companies.

And that’s worrisome. With the sudden surge in investment in AI, money is being thrown around like drunken sailors on a shoreside binge. And for the last ten years, that wild spending has become the prime catalyst for investment and growth of the US economy, creating some jobs and destroying many others. What happens if that investment turns out to be the latest financial bubble, and the spending suddenly collapses? If that occurs, not just the US economy but the European and global economies may well buckle like they did following the housing bubble collapse in 2008.

Is AI investment turning into a bubble?

The big Silicon Valley companies are investing heavily, but it’s not just on the AI technology itself. They also are mega-investing in gargantuan data centers and server farms that are the infrastructure backbone of this development. Google, Amazon, Meta/Facebook and Microsoft collectively spent around $400 billion on AI in 2025. Morgan Stanley analysts estimate that big tech companies will invest about $3 trillion on AI infrastructure through 2028. This is a massive influx of capital that is currently replacing consumer spending and traditional manufacturing as the main engine of US economic expansion. Germany and the EU are also undergoing a significant build-out of data centers, so the issues starting to rankle the US political economy will almost certainly emerge in Germany and the EU at some point. 

Here’s what’s troubling about the latest rounds of AI investment. To avoid burning up their own cash, instead these companies are taking on large amounts of debt to cover about half of the needed investment. A Goldman Sachs assessment found that key tech firms have taken on $121 billion in debt over the past year, a more than 300% uptick from the industry's typical debt load. Silicon Valley is taking on all this new debt with the assumption that massive new revenues from the invention of new AI-based products and services will cover the tab. But there is reason for doubt.

For example, the leading AI innovator, OpenAI, claims that it is planning to spend $1.4 trillion over the next eight to ten years on AI data centers and infrastructure, but its current annual revenue is no more than $20 billion. Most experts are in agreement that the current pace of investment in AI infrastructure far exceeds any foreseeable returns. The numbers just don’t add up. 

In the meantime, not just the level of debt but the type of debt and financing that these companies are taking on is causing major concern. It goes by odd names like “circular funding” and "special purpose vehicles,” which sound reminiscent of the shaky financial practices used leading up to the housing bubble in 2007-8. 

For example, recently Nvidia pumped $100 billion into industry leader OpenAI to bankroll the building of more data centers. OpenAI then is supposed to use that money to purchase Nvidia chips that will be used in the data center. In other words, Nvidia is subsidizing one of its biggest customers, giving OpenAI money to buy Nvidia chips, artificially inflating and propping up the price as well as actual demand for Nvidia chips. Meta also has a similar $27 billion private debt deal with Nvidia. 

By other measures, such as the S&P 500 price to earnings ratio (P/E ratio), today’s stock prices are so inflated that they are even higher than the dot-com bubble's peak. Like an investment casino, a huge amount of money has poured into the AI sector in a very short period of time, to the point where even the CEO of Google, Sundar Pichai, says there are “irrational elements” in the investment patterns right now. Pichai says if the market crashes the damage will be widespread; even highly capitalized Google will not be immune.

AI jobs being created – but not a lot of them, and some are dangerous

With the current wave of investment in AI driving the economy, the hope is that investment spending will create a wave of new services and businesses, and with it a lot of high-tech, highly paid jobs. But the vast amount of investment going towards data centers is not likely to create many jobs. Data centers largely consist of file servers and networking equipment, so developers are aiming for minimally staffed “lights-out” environments. Which means even in large scale centers the number of ongoing “operational jobs” following construction will likely be minimal. During the construction phase, the construction jobs often total around 1500 skilled trade workers. But post-construction, only about 100 operational jobs will continue in each data center, a small number of technicians, engineers and operators to keep everything running. Hyperscale centers may comprise a million square feet of space and cost a billion dollars to build, but they are not likely to create a large number of jobs beyond the initial construction.

In addition, there are potential problems with the operational jobs – some of them are quite dangerous. Servers generate substantial heat, making internal cooling systems essential. Data centers use chemicals in cleaning processes and in water treatment systems for cooling towers and humidification. Battery rooms, cooling equipment, water treatment systems and cleaning processes are all places where workers can come into contact with hazardous substances, like lead-acid and lithium battery chemicals and refrigerants that can harm skin or eyes on contact. While some refrigerants are harmless, others pose risks, especially ammonia. Ammonia exposure requires flushing with water kept at a specific temperature range. And it doesn’t take a big spill to cause a problem, a splash is enough to cause significant injury if not washed off immediately. So emergency safety showers must be located close by so workers can reach them quickly. 

Critics say that, in the rush to build build build, the companies are not fostering a culture of safety. Negligence and rushed timelines already are contributing to tragic outcomes from a number of accidents, including: 

• A fatal electrocution in a data center when a worker died in Georgia from faulty temporary wiring which electrocuted the worker
• Fatal truck accident, when a construction worker died in Texas after being struck by a heavy-duty articulating truck
• A Google data center experienced an electrical explosion, seriously burning three workers near Omaha
• High crash rates at a Meta data center in Louisiana, which saw a massive spike in crashes partly due to unlicensed drivers of heavy vehicles.

So for jobs created at data center jobs, it will be important to design worker protections based on good labor practices and adequate training.  

While the Trump White House is pushing heavy investment in AI infrastructure, its own immigration and deportation policies have made it more difficult to hire the software engineers needed to staff data centers. Also, an estimated 30% of construction workers in the US are immigrants, including some who are undocumented, and there aren’t enough electricians in the US to meet the demand for laying wires to build data centers. So Trump’s policies such as mass deportations and harassment of immigrant communities are resulting in labor shortages that are limiting the growth of AI infrastructure by draining the supply of workers needed to build and wire such facilities.

Environmental impact, massive energy consumption

Another increasing concern with the rapid construction of data centers is the environmental impact. Inside a data center, thousands of servers run continuously, supported by cooling infrastructure and backup power systems, which use an enormous amount of electricity. This is driving up prices for everyday consumers. Bloomberg reports that, in recent years, wholesale electricity costs have gone up by as much as 257% in areas near data centers. Market reports show that in August 2025, there were more than 1100 data centres across the US, with almost 400 new centers being built. Construction Review reports that there are six mammoth data centers currently under construction that need to be fed by over one gigawatt (GW) of power—an amount sufficient to power 750,000 homes.

Goldman Sachs has estimated that building the necessary energy infrastructure for AI data centers will require $1.4 trillion in investment by 2030. But as the Wall Street Journal has reported, “If the AI hype is overblown or the tech industry doesn’t ultimately need as much electricity as projected, other customers would get stuck with the infrastructure costs.”

Whether the rapid pace of AI investment results in a financial bubble or a transformative boom – or a bit of both – will not be known for several years. In the dot-com crash from 2000-2002, the internet was a promising new technology but telecom companies over-invested in transmission facilities for internet traffic. When the dot-com bubble crashed in 2002, technology stocks dropped 80 percent and half a million people lost their jobs as the unemployment rate zoomed to 7% (and 10% in the tech sector). Twenty-three telecom companies went bankrupt, including the collapse of the telecom giant WorldCom, at the time the single largest bankruptcy in US history.

So bubble collapses can have catastrophic and widespread consequences, much like a cyclone ripping ashore. Just as the global internet networks got built, despite a worldwide financial collapse, so too will AI get built. There will be winners and losers that will emerge, though at this point it's not clear who the winners and losers will be.

Is Germany trying to join the AI gold rush? 

With so much money sloshing around the AI investment markets, and with the US and China leading the way, other nations are trying to keep the pace. The EU and Germany are trying to find their footing in this fast-moving terrain. 

Investment in German data centers is surging, driven by AI and cloud computing, with major tech firms like Google, Amazon, Nvidia and Microsoft committing billions for investment within Germany. This is leading to significant capacity expansion, particularly around Frankfurt, Berlin, Munich and Cologne, and making Germany Europe's leading hub despite energy grid challenges. Significant investments are projected, totaling over €24 billion by 2029, as Germany aims to become a digital powerhouse. The EU is also trying to close the technology gap, unveiling last year a €200 billion plan to promote AI development and triple the region's capacity for such systems by 2032.

According to this map, Germany now has over 450 data centers located in 68 different markets. Over 100 data centers are located in Frankfurt alone, and another 12 have already been approved. In fact, data centers have now become the leading source of electricity consumption in Frankfurt, accounting for up to 40 percent of the city’s total power demand – and the local energy supply is being pushed to its limits.  In Berlin and Brandenburg, the second largest data center hotspots, new construction and expansion will result in significant power demand for those data centers, which will further burden an already strained energy market.

Yet even with the billions of euros being invested, it is a small amount compared to the hundreds of billions being invested by the US and China in 2025 alone. Wolfgang Eppler, a researcher at the Institute for Technology Assessment and Systems Analysis (ITAS) in Karlsruhe, says the amount of the German investment pales in comparison to US spending levels. "When you look at what the US is investing — for example, $500 billion — [the German investment] is really just a drop in the ocean", he said.

And with the emphasis on Germany and the EU catching up with its international competitors, few voices seem to be raising contrary issues about the downsides of a financial bubble, or the impact on workers, or the environmental risks or rise in energy prices for home users. Indeed, Minister of Finance Lars Klingbeil (SPD) has rolled out the red carpet for Google's plans to invest €5.5 billion in Germany to expand its data centers and infrastructure. “This is exactly what we need right now", said Minister Klingbeil.

Hopefully he is right, and the whole AI investment frenzy doesn’t turn out to be the latest financial bubble that pops and leaves economic devastation in its wake. As Europe and Germany look to adopt approaches similar to those pursued by the US and China, it is important to keep in mind the political, economic and cultural differences between the two superpowers and Germany and the EU, as well as the risks such strategies will entail.