Large Czech manufacturers have emerged as genuine European leaders in robotics adoption, a fact that often contradicts the common perception of the country's industrial capabilities. According to the Czech Statistical Office's 2022 robotics survey, large firms with over 250 employees rank second in Europe for industrial robot adoption.
The national average of 6% adoption across all firm sizes is misleading, as it fails to highlight the significant divide between company sizes rather than positioning Czechia against other European countries. In reality, small and medium-sized firms lag significantly behind their larger counterparts when it comes to robotics adoption.
What the numbers show
The adoption of industrial and service robots among manufacturing firms varies significantly by company size. Small firms, those employing between 10 and 49 people, see a relatively low uptake at 7.2%, with an average of just 2.8 robots per firm. This increases markedly for medium-sized companies (50 to 249 employees), where 28.2% utilise robotics technology, averaging 5.8 robots per firm. Large firms, those with over 250 employees, exhibit the highest adoption rate at 64.3%, deploying an average of 36.6 robots per company.
In a European context, Czechia stands out among large manufacturing firms for its robot usage, ranking second in Europe for industrial robots specifically (34% of large Czech firms, against an EU average of 22%). The country ranks fourth overall when considering both industrial and service robots (36% against an EU average of 26%). The automotive sector leads this trend, with an average of 52 robots per firm in 2022.
What's holding smaller firms back
According to the AFI Business Environment Survey 2026, the primary barriers to wider systematic use of AI, robotics and automation among Czech companies are a lack of internal capacity or expertise (59%), concerns about data security (41%), high implementation costs (39%), and legal or regulatory issues (23%). These challenges disproportionately affect smaller firms, which often cannot afford dedicated in-house IT or security teams to manage complex technologies like AI. Additionally, the significant upfront capital required for implementing advanced systems is a major hurdle for small manufacturers who lack the financial flexibility of larger enterprises.
Where managed infrastructure helps
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Lack of internal capacity or expertise - A managed Kubernetes platform means the firm does not need to hire its own platform or DevOps team to run automation workloads.
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Data security concerns - Hosting on EU soil (Hetzner data centres in Nuremberg, Falkenstein and Helsinki), with data that never leaves the EU, addresses residency and security concerns as a technical fact, not a slogan.
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High implementation costs - Predictable managed pricing replaces the large upfront capital expenditure of building infrastructure and hiring staff in-house.
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Legal or regulatory issues - EU-based hosting and data handling are already aligned with GDPR and NIS2 at the infrastructure layer, reducing what the firm has to solve itself.
Who this is for
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Manufacturing SMEs with 50-249 employees piloting their first automation or AI workload.
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Companies that want data pipelines or machine learning workloads hosted within the EU instead of on US hyperscalers.
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Firms that do not want to hire a dedicated platform team just to run a handful of automation services.
Getting started
If this sounds relevant to your situation, get in touch at info@cybermindnet.eu.