# Artificial Intelligence in Czech Firms: Surprising Figures Beyond IT

> How Czech companies use AI, what benefits it brings and why results differ across industries.

- Canonical: https://techmates.io/en/blog/artificial-intelligence-in-czech-firms-surprising-figures-beyond-it
- Published: 2026-10-21
- Updated: 2026-10-21
- Author: Lubomír Žáček, Marketing Specialist
- Topics: AI

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**_The share of Czech companies using AI has nearly tripled in just two years. But what makes these figures particularly interesting is not the growth itself. It is the significant differences between industries. While four in ten travel agencies use artificial intelligence, fewer than one in five manufacturing companies do._**

Why is AI gaining ground faster in some industries than in others? And does lower adoption necessarily mean less potential? The answer may have less to do with the industry itself and more with the processes companies handle every day.

## Behind the Rapid Growth of AI Lie Significant Differences Between Industries

According to the latest detailed data from the [Czech Statistical Office's Information Society in Figures 2026](https://csu.gov.cz/docs/107508/0a2a6132-26cb-59bb-22be-8ae53b0ef4e1/06100526.pdf?version=1.3), 17.6% of Czech enterprises with ten or more employees used at least one AI technology in 2025, compared to just 5.9% in 2023. The share of companies using AI has therefore nearly tripled in two years.

However, the overall average conceals substantial differences between individual industries.

In telecommunications and computer programming, 61.8% of companies used AI in 2025. High adoption in the technology sector is hardly surprising. The more interesting findings come from other areas.

In publishing, broadcasting and content production, 53.1% of companies used AI. Among travel agencies and tour operators, the share reached 40.1%, followed by professional, scientific and technical activities at 33.3% and wholesale trade at 24.2%.

By contrast, AI adoption stood at 16.7% in manufacturing, 14.4% in retail, 7.8% in construction and just 6.1% in transportation and storage.

![Comparison of AI adoption across Czech industries. (Source: Czech Statistical Office, Information Society in Figures 2026).](@/assets/uploads/ai-adoption-across-czech-industries.webp "Comparison of AI adoption across Czech industries. (Source: Czech Statistical Office, Information Society in Figures 2026).")

**The share of companies using AI was therefore approximately 2.4 times higher among travel agencies than in manufacturing,** even though manufacturing companies often operate in far more technologically complex environments.

This does not necessarily mean that travel agencies are more technologically advanced than industrial companies. Instead, it raises an interesting question: to what extent is the pace of AI adoption determined by the industry itself, and to what extent by the nature of the work carried out within it?

## Artificial Intelligence Gains Ground More Easily Where Work Is Already Digital

Many of today's AI solutions primarily work with information, whether that involves text analysis, document search, content classification, summarizing documents, generating text and code or processing large volumes of data.

Statistics from Czech companies reflect this pattern.

According to the Czech Statistical Office, 13% of enterprises used AI to generate text or programming code in 2025, 10% used it to create images, video or audio, and 7% applied it to advanced text analysis. The same proportion of companies used machine learning.

By comparison, 4% of companies used robotic process automation using AI, while only 1% employed technologies capable of physical movement based on autonomous decision-making.

These figures do not explain the differences between industries on their own. However, they suggest that business adoption of AI remains strongly connected to digital information and tasks that do not require direct intervention in physical operations.

A travel agency, for example, works with offers, reservations, destination descriptions, customer requests and multilingual communication every day. Media and publishing companies process large amounts of text, images and other digital materials.

When the necessary information is already available in digital form and the results can be checked relatively easily before use, the path to the first practical AI application may be considerably shorter than for a process involving machinery, sensors or several legacy information systems.

## In Manufacturing, AI Does Not Have to Start on the Production Floor

Lower AI adoption in manufacturing does not necessarily mean fewer opportunities. The difference may lie in how difficult it is to implement the technology.

When AI needs to communicate with manufacturing equipment, warehouses, operational systems or multiple data sources simultaneously, technical integrations become more complex. Requirements for data quality, security, reliability and quality control also increase.

![AI can deliver value to manufacturing companies beyond the production floor. (Photo: Pexels)](@/assets/uploads/ai-can-deliver-value-to-manufacturing-companies-beyond-the-production-floor.webp "AI can deliver value to manufacturing companies beyond the production floor. (Photo: Pexels)")

The first meaningful AI application therefore does not have to involve the production line itself.

Manufacturing companies can start with technical documentation, order processing, internal reporting, searching company knowledge or customer communication. In these areas, AI can support everyday activities without requiring changes to the core manufacturing process.

The same principle may apply to logistics, construction and other industries with a significant physical component.

When identifying suitable applications, it therefore makes sense to start with a specific process. How much time does it regularly take? How often is it repeated? Is the necessary data available and usable? How difficult would integration with existing systems be? And most importantly, how will the company know whether the process actually works better after introducing AI?

The answers to these questions may be more important when deciding where to start than the industry in which a company operates.

## Company Size Still Plays a Significant Role

Major differences are not limited to industries. According to the Czech Statistical Office, 13.4% of small enterprises with 10 to 49 employees used at least one AI technology in 2025. Among medium-sized companies with 50 to 249 employees, the figure reached 28.8%, while adoption among large enterprises with 250 or more employees stood at 54.1%.

A similar pattern can be observed in broader digitalization.

In 2025, 34.6% of small enterprises, 60.6% of medium-sized companies and 83.1% of large enterprises had a high level of digital intensity, according to the Czech Statistical Office.

This indicator takes various digital technologies into account, including ERP and CRM systems, data analytics, cloud services, e-commerce and AI itself.

These figures do not prove that a higher level of digitalization automatically leads to greater AI adoption, particularly since AI usage is itself one of the components included in the indicator.

However, a well-developed technological environment can make it easier to connect new tools with existing data and systems and integrate them into everyday business operations.

## In 2026, the Focus Is Shifting from Experiments to Real-World Operations

A more recent perspective on business practice comes from a [survey conducted by Deloitte and the Czech Association of Artificial Intelligence](https://www.deloitte.com/cz-sk/cs/about/press-room/pruzkum-deloitte-a-caui-ai-prestava-byt-experimentem.html), published in April 2026. The survey involved 155 companies from various sectors of the Czech economy.

Unlike the Czech Statistical Office's statistics, this was a separate survey involving a smaller group of companies, meaning its findings cannot be directly generalized to all Czech businesses. Nevertheless, it offers useful insights into how companies are working with AI and the benefits they perceive.

A total of 73% of respondents said they already had an AI strategy or were preparing one. Meanwhile, 30% of the surveyed companies had successfully moved at least 40% of their AI pilot projects into production.

The findings suggest that artificial intelligence is gradually moving beyond isolated experiments towards practical applications. However, bringing pilot projects into everyday operations remains a significant challenge.

The differences in where companies actually perceive AI benefits are equally interesting.

A positive impact on efficiency and productivity was reported by 85% of respondents, while 64% noted improvements in decision-making and working with data. Another 52% reported benefits for innovation and product development.

By contrast, only 21% observed improvements in customer relationships, and just 18% reported a direct impact on revenue growth.

These findings suggest that the surveyed Czech companies currently perceive the greatest value of AI within their internal operations. The technology helps speed up work, process information and support decision-making, while a significantly smaller share of respondents report a direct impact on business growth.

However, there is an important distinction between a perceived benefit and a measured result.

## Using AI Does Not Automatically Mean Creating Measurable Value

According to the Deloitte survey, measuring results remains one of the weaker areas of current AI adoption.

A total of 44% of respondents had no systematic method for tracking AI usage, and only 7% used formal KPIs and regular monitoring.

Companies may therefore perceive improvements in productivity or efficiency without being able to consistently measure their actual impact.

This becomes particularly important when individual experiments are expected to evolve into solutions that can operate over the long term.

Before implementing AI, it may be relatively easy to anticipate time savings or cost reductions. What is more difficult is verifying whether those expected benefits have materialized, what additional costs have emerged and whether expanding the solution makes financial and operational sense.

Simply using an AI tool does not necessarily mean that a company is creating value proportional to its investment.

We explored a related topic in more detail in our article [Where Is AI Investment Heading, and What Is It Actually Delivering for Companies in 2026?](https://techmates.io/en/blog/where-is-ai-investment-heading-and-what-is-it-actually-delivering-for-companies-in-2026), which examines the gap between growing AI budgets, business expectations and the value companies actually achieve.

The ability to measure results matters not only for justifying investments but also for deciding which projects to develop further, where to invest in integration and scaling, and which initiatives should be adjusted or discontinued.

Without proper evaluation, even a promising experiment can gradually turn into a long-term expense.

## The Real Value of AI Depends on the Process, Not the Industry

Data published in 2026 reveal two parallel trends. Artificial intelligence is spreading rapidly across Czech companies, but the path towards practical implementation differs significantly depending on the industry, company size and the nature of individual processes.

A travel agency may be able to introduce AI relatively quickly when handling information and customer requests. A trading company may use it for document processing or data analysis. A manufacturing business may begin with internal knowledge, technical documentation or reporting before considering AI applications directly within production processes.

The same technology can eliminate hours of repetitive work in one company, help connect information across multiple systems in another, and in some cases fail to deliver sufficient value compared to the cost and complexity of implementation.

This is precisely why a high share of companies using AI in a particular industry does not automatically mean that the industry is achieving the greatest benefits. Similarly, lower adoption does not necessarily indicate less potential.

For business leaders, the most important question is therefore not how many companies in their industry already use artificial intelligence or how many AI tools they have available.

What matters most is the ability to identify a specific process where AI can deliver measurable improvements and then turn those improvements from an initial experiment into a functioning part of everyday business operations.