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By TJ SoftUpdated:

The Largest Server Rooms and Data Centers in Poland Where the Country’s Digital Infrastructure Is Located

Największe serwerownie i centra danych w Polsce gdzie znajduje się cyfrowe zaplecze kraju

When people think of artificial intelligence, they usually picture ChatGPT, Gemini, or Grok. Then come associations with models, layers, parameters, and all that complicated mathematics. Few people consider the fact that none of these tools operate in a vacuum. They need servers, vast amounts of energy, memory, and data centers that keep them running around the clock.

Modern data centers are the foundation of today’s artificial intelligence. Without them, it would not be possible to train models, store data, or serve users in real time. This sector is developing particularly rapidly in Poland. New facilities are being built, global players are investing, and Polish companies are increasingly developing their own computing infrastructure.

As a result, the country is becoming one of the region’s key infrastructure hubs. Reliable energy infrastructure, growing business demand, and access to qualified specialists create conditions that enable the development of AI projects in private companies, public institutions, and startups. And each of these technologies, from medical diagnostics to generative language models, begins in the same place: server rooms and data centers.

Data centers are infrastructure; their size is measured not by the amount of available memory or computing power, but by the server room area and the amount of power they can handle. In short, depending on requirements, the space can be filled with memory or processors.

The importance of the energy sector and power plants is also evident.

Further on, you will find an overview of Poland’s most important data centers and their significance for the development of artificial intelligence.

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Table of Contents

How Many Data Centers Are There in Poland?

The Polish data center market is developing extremely rapidly—not only are new facilities being added, but their scale is also increasing in terms of available power and technical floor space. According to a report prepared by PwC, by the end of 2022, nearly 140 facilities designed as digital data processing centers were operating in Poland. In Warsaw alone, the supply of commercial power capacity reached approximately 130 MW (equivalent to the simultaneous consumption of more than twenty thousand household kitchens while preparing a meal). Additionally, analyses by companies such as PMR Market Experts indicate that the capacity of Poland’s commercial data centers could exceed 500 MW by 2030, representing an increase of more than 400 MW compared with the beginning of the decade.

When it comes to technical space, the figures are equally impressive. One of the latest reports indicated that the total commercial data center floor space in Poland has already exceeded 119,000 m², with a further 50,000 m² currently under construction. Altogether, that is equivalent to approximately 24 full-size football pitches. In practice, the largest facilities in the country span hundreds of thousands of square meters or have tens of megawatts of power dedicated to IT equipment, demonstrating that Poland has entered the era of “hyperscale” data centers.

Most of these facilities are located in Warsaw and the surrounding area; 61% of data centers are situated there. Kraków is in second place (10%), followed by Poznań (8%).

Source: PMR

These figures point to a qualitative shift in the market: it is no longer just a matter of numerous small server rooms, but increasingly large campuses designed to meet the demands of artificial intelligence systems, public cloud, and wholesale colocation. This means that the infrastructure must be capable of handling enormous loads, both in terms of power capacity and technical space, and that Poland is becoming an increasingly attractive location for global investors.

Where does Poland stand compared to other countries?

Poland performs surprisingly well compared with other Central and Eastern European countries and is increasingly catching up with the largest Western markets. We are not yet in the “champions league” of data centers such as the Netherlands, Germany, or France, but in the region we are among the absolute leaders and are developing faster than many Western European countries.

Poland Against the Background of Central and Eastern Europe

In our region, the countries with the largest number of data centers are:

  • Poland,
  • Czech Republic,
  • Austria.

Of the three, Poland has the largest supply of technical space and the fastest growth in power capacity. We are estimated to be the growth leader across Central Europe. Hungary, Romania, and Slovakia lag far behind in terms of both capacity available to customers and the number of new investments.

Poland Compared with Western Europe

Here, the differences are greater, but the gap is narrowing quickly. The largest markets are the so-called FLAP:

  • Frankfurt,
  • London,
  • Amsterdam,
  • Paris.

Each of these cities has capacity measured in gigawatts, while individual new campuses reach 100, 200, or even 300 MW of capacity. That is several times more than the entire Polish market today. In addition, Germany, the UK, the Netherlands, and France also have data centers in other cities. However, the difference lies not only in scale but also in market maturity: those facilities serve global cloud service providers and the largest technology companies.

Nevertheless, Poland is catching up very quickly. Estimates indicate that our market could exceed 500 MW by 2030, which would place us in Europe’s “upper middle tier,” alongside Spain, Italy, and Sweden.

Poland as a Strategic Location on the Map of Europe

There are several reasons why Poland has become attractive to investors:

  • stable power supply and sound energy decisions,
  • a location between Germany and the Baltic countries,
  • a large domestic IT and telecommunications market,
  • growing demand for AI and cloud services,
  • favorable operating costs compared with Western Europe.

That is why more and more companies (both Polish and foreign) are planning to build large campuses near Warsaw, Poznań, and Kraków.

Against the backdrop of Central and Eastern Europe, Poland is a clear leader and is developing the fastest, both in terms of capacity growth and the number of new investments. Compared with Western Europe, we are still catching up with the biggest players, and the difference in scale remains noticeable, although the gap is gradually narrowing. At the same time, Poland is gaining increasing importance in the global artificial intelligence development chain, as modern data centers are becoming a key foundation for AI systems that require stable infrastructure, substantial power, and reliability.

https://www.pwc.pl/pl/artykuly/popyt-na-centra-danych.html

Physical data infrastructure is critical to artificial intelligence

To understand why data centers are the foundation of artificial intelligence development, it is worth looking at how modern machine learning models work. Every model requires three basic resources:

  • data,
  • memory
  • and computing power.

The more advanced the model, the greater the requirements. Generative systems process terabytes of data and operate in real time, placing high demands on infrastructure. Without stable, high-performance data centers, it is impossible to maintain or develop such services.

When a company implements a product personalization algorithm, medical image diagnostics, video analysis, speech recognition, or a demand forecasting model, all these tasks require fast processing of large datasets. A data center must provide not only stability, but also adequate throughput, cooling, power infrastructure, and physical security. In this sense, the server room is the foundation of every technological breakthrough.

In the context of Poland, this is particularly important because local companies are developing many artificial intelligence solutions. The medical industry uses the services of companies such as Infermedica, Deepflare, and Labplus. The financial industry invests in anti-fraud systems developed by Nethone. The e-commerce industry uses cart-based recommendation algorithms created by Synerise. All these companies need infrastructure capable of handling high workloads, and some of them, for legal or strategic reasons, require data processing to be located in Poland.

Three Types of Entities Building Poland’s Data Infrastructure

The domestic data center market can be divided into three main groups:

  • private Polish companies building modern server facilities and cloud services
  • government institutions developing their own computing resources and digitalisation projects
  • global operators investing in Poland by building data centre campuses and cloud regions

All these entities co-create an ecosystem that is becoming the foundation for the development of artificial intelligence in Poland. Each has slightly different priorities; however, the growing scale of AI projects is forcing the entire market to become increasingly efficient and resilient.

What exactly is a server room and data center

A server room is a single, specially prepared room housing servers, disk arrays, and network devices. Such a facility has its own cooling, backup power supply, fire protection system, and access control, allowing the equipment to operate continuously around the clock. A data center is a much larger facility consisting of multiple server rooms, supplemented by extensive power, cooling, and security infrastructure.

To describe the scale of a data center, three key parameters are usually considered. The first is the technical floor area, meaning the actual space allocated for server racks. The second is the available power capacity, which indicates how much energy can be used and what the facility’s expansion potential is. The third is the security class, which defines the level of redundancy and resilience to failures, described using so-called tiers. From the basic Tier I, through the most common Tier III in Poland, to the exceptionally demanding Tier.

Redundancy consists of backup components or entire systems that come into operation when the primary component fails or requires servicing. Its purpose is to ensure continuity of operation.

Data centers are not described by the amount of memory they can accommodate or by the amount of computing power they have. This is because the number of available petabytes of memory or PFLOPS of computing power depends on the hardware installed in the data center. Companies need different configurations; sometimes computing power is more important, and sometimes memory is.

Polish Private Companies as a Pillar of Computing Infrastructure

Poland’s data center industry is largely built on private companies that have been developing local facilities for two decades. These include Atman, Beyond.pl, Comarch, Netia, and T-Mobile Polska. Each of these companies has its own approach to the role of a data center and its own development history.

Atman: Poland’s largest data center operator

Atman is one of the most important companies in Poland in terms of server infrastructure. Its two main facilities in Warsaw, designated WAW 1 and WAW 2, are among the most advanced in the country. WAW 2 stands out for its capacity to scale up to several dozen megawatts of power. This level enables it to support large-scale projects involving machine learning models and stream processing.

For Polish companies using local infrastructure, Atman is often the first choice. Keeping data in the country is particularly important for regulated industries such as finance, healthcare, energy, and the public sector. Many services related to data analytics and AI projects use Atman’s servers because the operator provides extensive configuration options and high availability.

Atman

Beyond.pl: the only Rated 4 data center in Central Europe

Poznań is home to one of the most technologically advanced facilities in this part of the continent. Beyond.pl Data Center 2 is the only facility in the region to have obtained Rated 4 certification, corresponding to the highest level of fault tolerance. This means that the center can continue operating even in the event of a complete failure of part of its power or cooling infrastructure.

For several years, Beyond.pl has also been developing a vast server campus in Piotrków Trybunalski, which is ultimately expected to reach several dozen megawatts of power capacity. This type of investment is a response to the growing computational needs of AI projects, especially those requiring local data processing.

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Comarch Data Center: infrastructure for enterprise solutions

For years, Krakow-based Comarch has been developing its own data center, which serves numerous financial, insurance, and industrial institutions. The company operates both as a cloud service provider and as an infrastructure operator tailored to large business systems.

Comarch’s data center plays an important role in analytics and algorithmic projects because it integrates with the company’s broad software portfolio. In Poland, there is a clear trend toward creating hybrid cloud environments in which the local server room serves as the control layer for sensitive data, while the public cloud handles scalable modules.

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Netia and T-Mobile Polska: telecommunications operators as data providers

Telecommunications operators’ infrastructure plays a significant role in the development of AI in Poland. Netia and T-Mobile Polska operate their own data centers in Warsaw, Kraków, Katowice, and Wrocław. These server rooms are often chosen by companies seeking infrastructure directly connected to network services. Telecommunications operators typically offer comprehensive solutions, combining server rooms with data transmission and security services.

In practice, this means that companies developing artificial intelligence systems can combine computing power with direct access to the network, which is important for projects requiring stream processing.

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State Institutions and Government Projects Supporting AI Infrastructure Development

Poland also has its own computing resources developed within public institutions. In recent years, awareness has been growing of the importance of computing power for the development of science, public administration, and national security. As a result, initiatives related to a national cloud, medical data, and tools supporting research are emerging.

Academic Centers and Supercomputers

Several supercomputers used in scientific research and projects based on large datasets operate in Poland. Among the most important centers are the Poznań Supercomputing and Networking Center and the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. This group also includes AGH Cyfronet in Kraków, home to the Helios supercomputer, one of the most advanced computing systems in the country.

Helios was created as part of the European EuroHPC infrastructure and designed to handle tasks requiring very high computing power. Its key applications include scientific computing, such as modeling physical phenomena, environmental simulations, medical data analysis, and genomics-related projects. The system was built on a GPU-accelerated architecture, which also makes it highly effective for training artificial intelligence models and other tasks requiring parallel processing.

For years, Cyfronet has played the role of one of the pillars of Poland’s HPC infrastructure, and Helios is a natural extension of this tradition. Its computing power, measured in petaflops, places it among the leading supercomputers available in Central and Eastern Europe. At the same time, the center provides a working environment for scientific teams, medical laboratories, and projects using deep learning models, strengthening Kraków’s position as one of the most important high-performance computing centers in Poland.

The Helios supercomputer was used, among other things, in the development of the Polish language model Bielik.

National Operator of the National Cloud

An interesting example of public-private cooperation is Chmura Krajowa. The project was established as an initiative of the state and the financial sector, and now integrates local services with solutions from global providers. Within this ecosystem, public institutions can keep data in Poland while using international artificial intelligence tools.

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State institutions processing medical and administrative data

Several major projects related to the analysis of public data operate in Poland. The best known include medical registries, e-health systems, the PESEL database, and the statistical tools of Statistics Poland. These data are often used in research and in services supporting the public sector. The construction of commercial and state-owned data centers is highly significant for the security of such resources.

Global Operators and the Creation of Polish Cloud Regions

Alongside Polish companies and state institutions, investments by technology giants building their own data center campuses in Poland are of enormous importance. Thanks to them, the country has become one of the main computing hubs in Central Europe.

Google Cloud: one of the most important regions in the CEE region

In 2021, Google launched a cloud region in Poland. This means that data can be processed within the country, which is crucial for companies operating in regulated industries. Alongside the region, infrastructure comprising several data centers distributed across Mazovia was established. Although their exact locations are not publicly disclosed, it is known to be one of the largest technology investments in Poland.

This allows Polish companies to use services such as BigQuery, Vertex AI, Cloud Run, and tools for training machine learning models without having to transfer data outside the country.

Microsoft Azure Poland Central

Microsoft took a similar path by launching the Azure Poland Central region. It also opened several data centers intended to serve both the private and public sectors. This represents a significant qualitative change, as it enables the use of advanced artificial intelligence tools without the need to transfer data outside Polish jurisdiction.

Equinix: a global network of connections and the WA3 campus

Equinix is one of the largest data center operators in the world. Its WA1 and WA2 facilities in Warsaw have been operating for years, while the new WA3 campus near Nadarzyn will be one of the largest facilities in Europe. Equinix is particularly important for companies developing artificial intelligence, as it enables the rapid interconnection of various cloud and on-premises environments within a single network.

The Importance of Data Centers for the Development of Polish AI Companies

The growing number of domestic and international data centers has a direct impact on the development of Poland’s artificial intelligence ecosystem. Polish technology companies such as Synerise, Infermedica, Nethone, SentiOne, Nomagic, Surveily, and Eleven Labs can operate at a global level thanks to access to stable and scalable computing infrastructure.

Local Data Processing as a Regulatory Requirement and Competitive Advantage

In some industries, such as medicine, banking, energy, and insurance, processing data in Poland is a necessity. This enables domestic AI companies to train models on sensitive data without having to use foreign locations.

Faster experiments and lower testing costs

Access to local infrastructure makes model training costs lower. Network latency is reduced, and access to parallel processing techniques is simpler. As a result, Polish companies can experiment with and deploy new solutions more quickly.

Development of Generative and Reconnaissance Services

Companies such as Eleven Labs, which develop advanced speech synthesis models, require infrastructure capable of storing and processing large audio datasets. Similarly, Surveily, which analyzes footage from industrial cameras, needs a combination of low latency and high computing power.

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Energy, Cooling, and Sustainability as New Challenges

Every data center needs power and cooling. In the case of large facilities, these requirements reach levels comparable to those of small manufacturing plants. As demand for artificial intelligence grows, so does energy consumption. That is why Polish operators are investing in modern heat recovery systems, water-based cooling technologies, and photovoltaic installations.

The largest data centers in Poland are designed to achieve the highest possible energy efficiency. Beyond.pl boasts one of the lowest PUE ratings in Europe. Atman and Equinix are investing in installations that use renewable energy sources, as well as in hybrid power systems. These measures are important not only from an environmental perspective but also from a business standpoint, as energy costs are one of the main factors affecting the price of server services.

The Artificial Intelligence Technology Pyramid

The technological pyramid of artificial intelligence shows something many people forget: the entire process works from the top down, although the infrastructure we see is built from the bottom up.

AI Pyramid

How does this process work in practice

At the very top is the problem to be solved: a company, researchers, or an institution wants to create a system that will forecast demand, analyze medical images, generate text, translate speech, control production, or create simulations. Everything starts with this need.

Only then does the next question arise: what algorithms and programs will be needed to solve this problem? Models need to be designed, architectures selected, training environments prepared, and code written.

The next stage is data, because artificial intelligence cannot exist without it. Data is collected, processed, and prepared so that the system can learn. Only then do we get to the hardware layer, meaning the decisions: how much computing power is needed? how much memory? how many GPUs?

Next, the appropriate equipment is purchased. In small projects, purchasing computers, servers, or several accelerators is a matter of weeks or a few months. Here, the most important constraints are the budget and organization.

However, as requirements grow, the situation changes. The equipment has to operate somewhere, so it ends up in a server room, and at larger scales, in professional data centers. These are no longer ordinary air-conditioned rooms, but facilities with multiple power feeds, numerous cooling systems, physical security, and redundancy.

And here lies the biggest challenge: AI at scale requires enormous amounts of energy.

Where the real limitations begin

Building a data center takes a long time and costs a great deal. In Poland, the construction of a modern facility with a capacity of 20–40 MW is a project measured in years, not months. You need to:

  • acquire a plot of land,
  • obtain permits,
  • design the facility,
  • provide power connections,
  • build the technical infrastructure,
  • implement cooling and security systems.

All of this takes time, even if the investor operates very efficiently. The final layer of the technology pyramid is an even greater challenge: energy.

The construction of new power plants, the modernization of gas-fired units, renewable energy sources, or transmission networks are long-term investments, often spanning more than a decade. Costs run into billions of zlotys or euros. If computing needs grow faster than a country’s capacity to expand its power infrastructure, a constraint emerges that cannot be overcome with money or goodwill.

The Inverted Logic of the Pyramid

The pyramid therefore operates in two directions:

  • from top to bottom: needs → algorithms → data → hardware → server rooms → data centers → energy,
  • from bottom to top: the actual capacity of the infrastructure limits how much AI can be built in practice.

At a small scale, everything moves quickly and efficiently, because it is enough to purchase a few additional servers. At a large scale—the scale required for training language models, image recognition, or analytics at a global level—the main limitations lie not in programming, but in concrete, cables, cooling, and megawatts.

Therefore, the development of artificial intelligence is largely dependent on the infrastructure at the very bottom of the pyramid: data centers and energy. Everything the user sees at the top (models, applications, solutions) is possible only thanks to a stable, powerful, and long-term planned foundational layer.

How to quickly meet the growing demand for energy?

The growing demand for energy, especially when new equipment or infrastructure needs to be powered quickly, can be met by cheaper sources that can be built more rapidly. For example, a 50 MW photovoltaic farm is usually built in less than a year and costs approximately PLN 150–180 million (smaller, cheaper, and faster-to-build farms can also be constructed), while a modern gas-fired power plant with a capacity of 400–600 MW costs around PLN 2–5 billion and takes approximately two to three years to build. Such solutions make it possible to increase capacity flexibly, although the energy they produce can be more expensive, as production costs depend on fuel prices or weather conditions.

Capital-intensive investments, above all nuclear power plants, are entirely different. Building a single 1–1.6 GW unit typically costs PLN 25–45 billion and can take as long as ten years. Once commissioned, such a unit operates almost continuously, supplying inexpensive energy for several decades. The cost of generating electricity itself is exceptionally low because fuel accounts for only a minimal share of total expenditure. For this reason, the energy system usually combines fast-to-build, less expensive sources to meet immediate growth in demand with costly but stable power plants that provide long-term predictability and low energy prices.

Scientists and Specialists Are a Vital Piece of the Puzzle

In the technological pyramid of artificial intelligence, scientists and specialists stand alongside all the layers, because their work concerns every stage of creating and maintaining the system. This includes not only people responsible for algorithms and data, but also teams working on infrastructure: server administrators, power engineers, cooling and network specialists, and even physical and cybersecurity teams. Some tasks can be performed remotely, but many operations require their presence on site, at the infrastructure itself. Configuring GPU clusters, testing hardware, maintaining power systems, working on cooling, inspecting server rooms, and conducting energy and security audits—all of this requires people, time, technical facilities, and ongoing maintenance costs. Therefore, in this pyramid, experts are not merely one layer, but a constant support for the entire structure, from the initial concepts of the model to the physical operation of the facility that must sustain it.

What exactly is a server room and data center

As I wrote earlier, a server room is a single room or a small space where servers, disk arrays, and network devices operate. Such a place must have a constant temperature, backup power, adequate cooling, fire protection, and monitoring. All this is to ensure that the equipment can operate reliably around the clock.

A data center is a much larger facility. It can be said to consist of multiple server rooms, complemented by comprehensive power, cooling, and security infrastructure. It is not merely a collection of computers, but an entire infrastructure designed to process data quickly, continuously, and securely. In the context of artificial intelligence, this is of enormous importance, as modern models are highly demanding in terms of computing power and energy.

How to Determine the Size of Data Centers?

The scale of a data center is determined using three basic parameters:

  • Technical floor area meaning the actual space designated for server racks.

  • Power capacity indicating how much energy the facility can consume and the extent to which it can be expanded.

  • power density how many kilowatts can be connected to a single rack (critical for AI)

  • Security class confirmed by certificates specifying fault tolerance and the level of redundancy.

This third element is precisely the key. It determines how the facility will behave in a crisis situation. In Poland, most data centers are Tier III, as they offer very high availability while not generating enormous maintenance costs.

Why don’t we talk about available memory or computing power in the context of data centers?

A data center is not described by its memory capacity or computing power, because it is not a single computer but rather infrastructure that enables computing equipment to be installed. Customers place their own servers, disk arrays, and GPU devices there, and their specifications may change at any time. If a data center were described by the number of terabytes or TFLOPS, this value would be unstable and depend solely on what equipment happens to be inside at any given time.

Instead, a data center is described by what remains constant: technical space, available power capacity, and security class. These are infrastructure parameters, not computer parameters. Only on this foundation do customers build computing environments tailored to their needs.

You can think of a data center as:

  • a garage for cars
    it is not described by the power of the engines in the cars, but by how many parking spaces it has and what installations it includes,
  • a logistics hall it is not described by the weight of the goods, but by its area, load-bearing capacity, and infrastructure,
  • a shopping center one does not say how many stores will sell goods there, but rather what area and utilities it has.

Technical Area

Technical space is one of the most important concepts in the world of data centers, although at first glance it sounds very simple. In practice, it refers to the actual, available space intended for server racks and infrastructure that directly supports computing equipment. It therefore does not mean the entire building, but only the part where devices that operate around the clock are actually located.

It is precisely the technical floor space that determines how much equipment can be installed in a facility and how extensively it can be expanded in the future. Its size translates into the number of RACK cabinets that can be installed, the installation density, and whether the data center is suitable for running advanced artificial intelligence systems. This is particularly important in the case of AI, because GPU servers consume significantly more energy and generate more heat than conventional machines. The larger and better designed the technical floor space, the easier it is to build an environment capable of sustaining such workloads.

It is worth remembering that the space itself is not merely empty square footage. It must be equipped with appropriate technical flooring, cooling systems, cable routes, and power supplied in such a way that every device has reliable and stable operating conditions. That is why technical space is treated as a premium resource. It is a factor that determines whether a given data center can support advanced projects, as well as how much additional infrastructure can be added without reconstructing the entire facility.

Put simply: the larger the technical space, the greater the flexibility, scalability, and capacity of the data center to handle growing computational needs, especially in projects related to artificial intelligence.

Energy Capacity

Power capacity is a parameter that determines how much energy a data center can deliver to the equipment operating within it. In practice, it indicates the maximum amount of energy that can be supplied simultaneously to servers, disk arrays, cooling systems, and all supporting infrastructure. It is one of the most important indicators because modern computing environments, especially those used in artificial intelligence projects, are highly energy-intensive.

When we look at power capacity, it is not merely a question of whether the facility has a sufficiently powerful connection. What also matters is the ability to deliver power reliably to every server rack, redundancy in the power supply lines, and how the facility will perform under sudden load spikes. GPU servers can consume several times more power in an instant than traditional machines, which is why data centers must have appropriately designed infrastructure to handle such fluctuations without the risk of downtime.

High power availability translates into the ability to install high-density compute racks, which can reach anywhere from a dozen to even several dozen kilowatts per individual rack. These configurations are required for training generative models, video analysis, and real-time data processing. Without adequate power, a data center cannot ensure stable server operation or maintain the proper temperature, as cooling systems also consume energy and operate proportionally to the load.

Therefore, power capacity is one of the key elements when comparing data centers. The greater it is and the better it is managed, the greater the opportunities for growth and scaling.

Data security levels.

The Uptime Institute introduced four classes describing infrastructure resilience to failures.

Tier I

The simplest level. It provides basic power and cooling, but does not have full redundancy. Suitable for small local server rooms.

Features:

  • no redundancy,
  • risk of downtime during servicing.

Tier II

This is a level with partial redundancy. It adds backup components, such as additional cooling or power lines.

Features:

  • basic redundancy,
  • shorter downtime in the event of failures.

Tier III

The most popular tier in Poland. It enables infrastructure maintenance without interrupting system operations.

Features:

  • full redundancy of critical components,
  • ability to operate even if one system fails,
  • high availability.

That is precisely why Tier III is the standard chosen by companies working on AI.

Tier IV

Highest level. The facility continues to operate even if one of the main infrastructure components stops functioning.

Features:

  • full and multilayered redundancy,
  • minimal downtime,
  • very high construction and operating costs.

They are rare in Poland. The most common are extensive Tier III solutions, functionally approaching Tier IV.

Why Are Tier Classes So Important for Artificial Intelligence?

AI projects require stability, low latency, and substantial computing power. Generative models need powerful GPUs, video analysis must operate in real time, and predictive systems cannot afford to stop.

Therefore, the data center must provide:

  • reliable power supply,
  • efficient cooling,
  • resilience to failures,
  • the ability to quickly scale up capacity.

For this reason, companies developing AI tools choose Tier III or Tier IV facilities. Only such data centers are capable of meeting the growing computational demands.

Types of Server Rooms and Basic Differences

Server rooms differ in scale, design, and purpose. They are most commonly divided into two main types.

Local Server Rooms

These are small rooms in companies or institutions. They are used to meet basic needs, such as:

  • operation of internal systems,
  • storage of local data,
  • basic network infrastructure.

Such server rooms are important, but they are not suitable for large-scale artificial intelligence projects. They lack redundancy, sufficient power capacity, and scalability.

Professional Data Centers

These are facilities designed from the outset for continuous operation. They are distinguished by:

  • multi-path, independent power supply,
  • redundant cooling systems,
  • advanced physical security measures,
  • the ability to easily expand power and space.

It is precisely in such data centers that artificial intelligence systems are deployed, from business analytics to generative language models.

Server A computer designed to operate continuously. It provides resources to other devices, such as applications, files, or a database.

Server Room A single room prepared for server operation. It has its own cooling, backup power supply, and security systems.

Data center A large facility consisting of multiple server rooms, with extensive power, cooling, and security infrastructure.

RACK / server cabinet A metal cabinet in which servers and network devices are mounted. It has a standard width, and its height is specified in “U” units.

U Unit (rack unit) A unit of height in server racks. 1U is 4.445 cm. Standard servers are 1U or 2U high.

UPS (uninterruptible power supply) A device that maintains power during short-term outages. It protects servers from sudden shutdowns.

Redundancy Backup components that take over operation in the event of a failure. It may concern power supply, cooling, or network connections.

Tier (security classification) Classification of data centers according to the Uptime Institute. It defines a facility’s resilience to failures: Tier I is the lowest level, while Tier IV is the highest.

PUE (Power Usage Effectiveness) Energy efficiency metric. It indicates how much energy reaches the servers and how much is consumed by the rest of the infrastructure.

Precision cooling
A server cooling system ensuring stable temperature and humidity. More efficient than traditional air conditioners.

Access control A physical security system, such as cards, biometrics, monitoring, and entry logs.

Power density The amount of power that can be delivered to a single server rack. Critical in AI projects, where GPU racks may require up to 40 kW.

Colocation A service involving the provision of space in a data center for the client’s equipment. The data center provides power, cooling, and security.

Public cloud
A set of computing services provided by global providers, such as Google, AWS, or Microsoft. The hardware is located in their data centers.

Hyperscale Very large-scale data centers, most often built by cloud companies. They have hundreds of thousands of square meters and hundreds of megawatts of power.

HPC (High Performance Computing) High-performance computing performed on supercomputers or clusters. Used in science, physics, data analysis, and AI.

GPU server A server equipped with graphics processing units designed for parallel computing, essential for training AI models.

Failover Automatic switching to a backup system in the event of a primary system failure.

Load balancing Evenly distributing the load among multiple servers to improve performance and prevent overloads.

Poland as a Growing Artificial Intelligence Hub

The connection of national data centers with Google and Microsoft cloud regions and global networks such as Equinix has made Poland one of the most important computing hubs in Central Europe. This infrastructure development enables Polish startups to compete in the global market, while government institutions gain access to top-quality analytical tools.

As a result, a structure is created that enables the rapid implementation of new technologies. Language models, analytical systems, generative tools for business, anti-fraud systems, and medical algorithms are developing at a pace largely driven by the availability of computing infrastructure. This is precisely why data centers are becoming the foundation of a new stage of digital transformation in Poland.

Summary

The largest data centers in Poland play a key role in the development of artificial intelligence. They enable model training, the processing of vast datasets, and the operation of real-time applications. Polish private companies, state institutions, and global operators are working together to create an ecosystem that places the country at the center of Europe’s technological revolution.

If you wish, I can also prepare a second part of this article about the future of server rooms in Poland, liquid cooling, planned investments through 2030, or how data center architecture will change in the era of generative AI.