Data Centers Nearing Capacity Limits as AI Absorbs Nearly All Spare Infrastructure

Global data center infrastructure is approaching its capacity limits faster than expected just a year ago. According to the latest estimates from Goldman Sachs Research, utilization of existing facilities will rise from 85 percent in 2023 to more than 95 percent by the end of 2026, driven primarily by the surging demand generated by artificial intelligence models.

The problem isn't just the number of server facilities, but the fact that infrastructure designed over the years for classic processor-based workloads can't keep pace with the demands of the graphics chips used to train and run large language models. The gap in power requirements is more than tenfold, forcing a rebuild of electrical installations, cooling systems and entire data center architectures.

Where the Deficit Comes From

A traditional server rack drew between 3 and 8 kilowatts of power. A rack filled with the type of graphics chips used to train AI models needs between 30 and more than 100 kilowatts. That means the same physical data center floor space must now handle a power draw more than ten times greater, along with entirely different requirements for cooling, backup power and network cabling.

Operators who built their facilities around cloud computing and standard business applications are now facing the need for deep modernization or entirely new builds from the ground up. That process takes months, and years for large investments, while demand for computing power keeps climbing month over month.

The pace of growth in demand for computing power is starting to outstrip the technical capacity of existing infrastructure - Andrzej Bocheński, Director of the Data Center Division at Polcom

Scale of Global Investment

The AI infrastructure market as a whole is projected to reach $394.5 billion by 2030, growing at a rate of 19.4 percent per year, according to MarketsandMarkets data cited in industry analyses. The data center segment built specifically for AI workloads is expected to grow from $236.44 billion in 2025 to $933.76 billion in 2030, an average annual growth rate of 31.6 percent.

McKinsey goes further, estimating that building and modernizing data centers for AI alone will require global spending of around $5.2 trillion through 2030. That figure is comparable to the annual GDP of a large European economy, and it covers just one segment of digital infrastructure.

Poland's Perspective

Poland remains the largest data center market in Central and Eastern Europe. According to analytics firm Audytel, the country's commercial data centers already occupy more than 119,000 square meters, with another 50,000 square meters under construction. That scale, however, remains modest compared to the global demand generated by companies training and running AI models at mass scale.

For Polish operators and companies planning their own AI deployments, this cuts two ways at once - growing pressure to build new, power-hungry facilities on one hand, and rising costs of accessing cloud computing power on the other, if global demand outpaces supply faster than the announced investments can close the gap.

What Comes Next

The data center industry is responding to the shortage on several fronts at once - investing in liquid cooling, new power architectures and locations closer to sources of cheap energy. At the same time, regulatory constraints are becoming more common, such as the earlier halt on construction of large AI data centers in New York, showing that infrastructure pressure is already colliding with local social and environmental pushback.

If Goldman Sachs' forecasts hold, the second half of 2026 could be the moment when the computing power shortage becomes a real brake on further AI adoption at companies, regardless of how fast the models themselves keep improving. Sources: AI Could Exhaust Data Center Infrastructure Capacity by the End of 2026 (executivemagazine.pl), AI Could Exhaust Data Center Infrastructure Capacity by the End of 2026 (isbtech.pl)