# How many companies actually use AI? Global and Czech data

> In the last two years, artificial intelligence has shifted from an experimental technology to standard business practice.

- Canonical: https://techmates.io/en/blog/how-many-companies-are-actually-using-ai-global-and-czech-republic-data
- Published: 2026-04-14
- Author: Lubomír Žáček, Marketing Specialist

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In the last two years, artificial intelligence has shifted from an experimental technology to **standard business practice.**

But how many companies are truly using it, and how does the Czech Republic measure up?

Current data shows that while adoption is skyrocketing, a massive gap remains between **the first experiment** and **actual business value.**

### AI is no longer a marginal technology

According to the [Stanford AI Index](https://hai.stanford.edu/ai-index/2025-ai-index-report) 2025, 78% of organizations were using AI in 2024, which is a significant year-over-year jump from 55%. The rise of generative AI (GenAI) is even more aggressive, with usage increasing from 33% to 71%.

Investment trends tell the same story. [Gartner](https://www.gartner.com/en/newsroom/press-releases/2025-03-31-gartner-forecasts-worldwide-genai-spending-to-reach-644-billion-in-2025) estimates that global spending on GenAI will reach 644 billion USD in 2025, which represents a 76% increase. Companies are no longer just testing the waters. They are betting heavily on AI because they view it as **a key to efficiency in an era of rising costs.**

![Digital world map over binary digits, figures and chart lines](../../../assets/uploads/migrated/post-how-many-companies-are-actually-using-ai-global-and-czech-republic-data-body-1.jpg)

### Pilot projects versus real transformation

However, high adoption does not automatically mean high maturity. McKinsey points out that less than a third of companies follow recommended best practices for scaling AI. Many organizations end up in the so-called pilot trap. They have dozens of interesting prototypes that never actually generate revenue or save costs.

True competitive advantage **does not come when a team tries out a chatbot.** It emerges only when AI is integrated into company data, processes, and KPIs. This is what separates an interesting experiment from a true transformation.

### The European context and Czech reality

While global corporations report high numbers, [Eurostat data for 2025](https://ec.europa.eu/eurostat/web/products-eurostat-news/w/ddn-20251211-2) is more grounded because it includes the small and medium enterprise (SME) segment. Across the EU, 20% of enterprises use AI, which is a jump from 8% in 2023.

The Czech Republic, [at 18%](https://csu.gov.cz/produkty/v-pouzivani-ai-dohani-podniky-v-cesku-prumer-eu), is quickly **closing in on the European average.** In one specific discipline, we are even ahead. This is the use of GenAI for creating text and code, where in Czechia we see 13% compared to 9% in the EU. This highlights typical Czech resourcefulness. Czech companies have been very quick to adopt accessible tools with a low barrier to entry that bring immediate effects to marketing, administration, or software development.

![Night view of a crowded, illuminated square in Brno beneath the Cathedral of St Peter and Paul](../../../assets/uploads/migrated/post-how-many-companies-are-actually-using-ai-global-and-czech-republic-data-body-2.jpg)

### Sector differences: who leads and who waits?

Adoption in the Czech Republic is not uniform. According to 2025 data from the Czech Statistical Office (CZSO), the situation is as follows:

- Major players: [54.1% of large enterprises](https://csu.gov.cz/docs/107508/e853d9db-fc55-661d-ec4e-a16d8933ee6a/06200525t10.pdf?version=1.3) benefit from abundant data and innovation budgets.

- Traditional segments: Adoption remains low in [transport (6.1%) and construction (7.8%)](https://csu.gov.cz/docs/107508/e853d9db-fc55-661d-ec4e-a16d8933ee6a/06200525t10.pdf?version=1.3).

**This gap is not just about a lack of interest.** In sectors dominated by physical processes and low levels of digitalization, AI implementation is far more complex. It requires modernizing systems, standardizing data, and often a shift in mindset across the entire operation.

### Conclusion: AI in 2026. Fewer presentations, more execution

The data suggests three clear conclusions for strategic planning:

1.  AI is mainstream: It is no longer an optional add-on for tech enthusiasts but an essential part of business reality.

2.  The barrier is process, not technology: Today, companies struggle most with how to integrate AI into existing structures while ensuring data security.

3.  The Czech Republic has a great start: The true potential now lies in moving from simple chatbots to complex solutions that can predict demand, optimize logistics, or provide deep personalization of the customer journey.

In 2026, it will not be enough to **simply follow trends** or **collect tech news.** The deciding advantage will go to those companies that can identify areas with the highest real impact, test AI there safely, and then fully integrate it into their daily operations.

Real transformation **does not happen on paper,** [**it happens in practice**](/en/ai-transformation)**.**