Introduction

The race to dominate artificial intelligence and the industry is creating enormous investment opportunities. Technology companies continue to compete for scarce resources such as electricity, computer chips, and infrastructure. Due to the nature of these resources well funded companies will have bidding wars for the limited supply and outspend everyone else. The costs get passed along with businesses facing higher input costs raising their own prices.Once the rate rises, it rises for all buyers, not just the big ones. The rest of the economy now has to deal with that continuously higher price level.

The World's Most Expensive Technology Race

Artificial intelligence has become one of the biggest investment stories of the decade. Companies such as Microsoft, Alphabet, Amazon, and Meta are pouring enormous sums of money into building the framework needed to develop and operate AI. Behind the scenes of every chatbot, automated assistant, and AI-generated ads are a network of data centers, computer chips, cooling systems, and infrastructure.

The scale of how much investment is going into AI is remarkable. According to the International Energy Agency (IEA), capital spending by major technology companies exceeded $400 billion in 2025 and is expected to increase by another 75% in 2026.

This amount of spending reflects the belief that artificial intelligence will change entire industries and create substantial future profits. However, the AI boom raises a less obvious economic question: When companies invest so heavily in artificial intelligence, what happens to everyone else competing for the same resources?

The answer to his question goes beyond just the technology industry. AI’s expansion is creating additional demand for electricity, specialized equipment, construction, and financing. When the supply for these limited resources cannot keep pace with the demand, costs rise, potentially affecting business and households by hiring prices for electricity and electrical equipment despite having little direct involvement in AI.

The Electricity problem behind Artificial Intelligence

One of the main problems behind expanding AI is electricity. Data Centers need substantial amounts of power in order to operate both servers and cooling systems. As AI models are becoming more widely used, companies are building additional facilities to meet the growing demand. However, electricity infrastructure cannot always build at the speed that technology companies want them to.

The IEA reported that the global data-center electricity consumption increased by 17% in 2025, while electricity consumption at AI-focused data centers grew by 50%. Its analysis projects that total data-center electricity consumption could double that amount between 2025-2030. The speed at which technological development is growing is clearly a mismatch for the time required to expand electricity generation and infrastructure.

This brings up the question: who ultimately pays for the additional infrastructure? According to researchers from the MIT Center for Energy and Environmental Policy they found that data-center entry between 2010 and 2024 was associated with a 2.1% increase in average residential electricity prices, alongside even larger increases for commercial and industrial customers. This does not mean that every new data center will increase household electricity bills but nevertheless it suggests that data-center expansion creates costs that extend beyond the companies that build those facilities.

The Hidden Cost of Competing for Resources

The resources are more than just costly. Electricity is only one of the problems with a single large AI data center using as much power to run a small city which runs 24/7. Large plots of land are required to be near a strong power supply and more than often a water source for cooling, narrowing down the options on where they can go. Advanced semiconductors eat up tens of thousands of specialized chips to train and run the AI models. Specialized equipment is required due to the heat that the chips generate so specific industrial cooling systems are needed on top of generators and batteries that keep them running 24/7. Transformers are a piece of electrical equipment that changes the high voltage power made for data centers to a usable level for homes.

When a company or industry competes for limited resources, the resulting demand experiences weakness in other areas such as financing and the delay of projects. Due to the fact that AI infrastructure requires so much upfront investment, companies must decide whether to pour all their available capital toward data centers, existing operations, research, or different projects.

Let's say a company has to decide between expanding its current manufacturing operations and investing in AI infrastructure. By choosing the AI project, it gives up the opportunity to use that money elsewhere. If the technology improves productivity and creates profit the investment ultimately benefits the company. The problem here is that all the companies are simultaneously pursuing this interest. All capital, labor, and energy is flowing towards AI and away from any other uses. The economic impact depends on whether the returns from AI justify the resources consumed.

The Real Price of the AI Revolution

Artificial Intelligence is often discussed in the terms of its potential to replace jobs, transform industries, or create the next generation of technological advancements. Less attention is paid to the physical and financial resources it takes to make those changes possible.

The current AI boom shows that just because of the technological progress that society has made it does not occur independently of the wider economy. Even digital products need physical means from electricity, equipment, infrastructure, and capital. When demand for these resources grows rapidly, the effects can go so far to reach industries and consumers not related to the technology sector.

If AI generates substantial productivity gains while infrastructure keeps pace with demand, the technology could ultimately reduce costs across various industries. On the other hand if resources are scarce and infrastructure expenses are poorly managed, the gains are offset by higher costs. Overall the AI gold rush may create enormous wealth however whether it makes the economy more productive or more expensive will depend on whether supply can keep up with demand without driving up costs.

Sources:

The Hidden Economic Cost of the AI Gold Rush

Introduction

The World's Most Expensive Technology Race

The Electricity problem behind Artificial Intelligence

The Hidden Cost of Competing for Resources

The Real Price of the AI Revolution