Will AI Replace Customer Service Jobs in Czech Republic? Here’s What to Do in 2025

This guide explains what to expect for customer‑service jobs in the Czech Republic in 2025: where AI is already concentrated (healthcare, banking, manufacturing and customer support), what the evolving regulatory backdrop looks like, and practical steps employers and workers can take right now.

Estimates put AI use in Czech firms between roughly 35% and 40%, and research warns generative AI could affect over 2.3 million workers, so the stakes are tangible.

For grounding on adoption trends, see the Axevera analysis of AI in Czech companies, and for the policy and legal context consult the Global Legal Insights chapter on Czech AI strategy and regulation; for hands‑on upskilling, Nucamp's 15‑week AI Essentials for Work course teaches practical prompt skills and workplace AI applications.

“The advent of artificial intelligence represents a significant opportunity for the transformation and modernisation of Czech industry. That is why we at the Ministry have decided to assume the leading role in implementing AI into the Czech legal system and to actively support its development and practical application.”

Current adoption in the Czech Republic is best described as uneven momentum: headline figures range from about 11% of firms using AI (matching Eurostat and national surveys) to far higher use in larger companies - 41% of big enterprises report AI tools - while sector surveys put some creative firms at roughly 28% today with expectations to reach half within three years; see the detailed Adastra analysis of Czech AI adoption and use cases and the Global Legal Insights: Czech AI strategy and regulation overview for the full picture.

Growth is real but cautious: gaps in infrastructure, quality data, skills and a cultural reluctance to move quickly from pilots to full operations slow scaling, even as practical wins - like Hyundai's AI planning that collapsed hours of scheduling into five minutes and saved CZK 13 million - show rapid payoff when projects are done right.

National initiatives (NAIS) and funding calls such as TWIST are nudging more companies to invest, but regulatory alignment under the EU AI Act and the need for cross‑company innovation networks remain decisive factors that will shape whether these early experiments become routine tools in Czech customer support and operations.

For businesses and workers, the takeaway is clear: pick demonstrable, fast‑win projects and build the data and skills to scale them.

"The democratisation of artificial intelligence is essential to ensure that its benefits are not the preserve of global players such as Google and Amazon, which are implementing AI at tremendous speed." - Roman Berglowiec, Everbot (survey quoted in Screenvoice)

In Czech customer service, AI is nudging jobs away from repetitive work and toward oversight, model‑management and higher‑value interaction: large employers are actively hiring AI specialists - see the Vodafone Czech Republic AI Expert role, which centers on AI solution development, NLP and cross‑team advisory - while consultancies such as EY describe AI as a tool to upskill and

give people time and headspace for more critical thinking and creativity

rather than simply replace them; experts nonetheless warn some roles remain vulnerable (see the Expats.cz roundup of jobs most at risk).

Practical changes are already visible in tooling and workflows - for example, merchant helpdesks can use solutions like Yuma AI for in‑ticket returns and refunds to cut resolution time - so new staff tasks tilt toward prompt design, exception handling, data quality and customer empathy.

The net effect in 2025: more hybrid roles that pair service knowledge with basic ML/NLP literacy, and clear opportunities for agents who learn to work with models and to turn model outputs into trusted customer outcomes.

Designing Czech customer support in 2025 means accepting a clear trade‑off: speed wins when systems are imperfect, but humans still matter when emotions or complexity spike.

Research from Daktela's MNForce survey found Czechs are fed up with long waits, being bounced between agents and missing order details - and nearly 80% would rather get a bot reply in 3 minutes than wait 3 days for a human, while a majority prefer a robot that answers in 3 seconds over a slower human lookup; these are hard signals to ignore for any CX roadmap (Daktela MNForce survey on Czech customer support preferences).

At the same time, reporting on CX design stresses that empathy and seamless escalation remain essential: speed and automation must be paired with visible, frictionless handoffs to people for urgent or emotional cases (Rethinking customer experience in the age of AI).

Practical service design for Czech firms should let customers self‑select fast bot help for routine tasks, preserve full context across handoffs, and keep an obvious “human escape hatch” for complex issues - an approach backed by broader surveys showing most customers want AI for quick wins but still choose humans for nuance.

The memorable test: if a bot can resolve an order problem in seconds, many Czech customers will cheer that instant result - provided a human is waiting on the other end when things get sticky.

"We offer small and large businesses a free email analysis and AI bot setup to save them time in their daily routine. Our AI EmailBot will learn how to respond to what based on previous email communications over two days. It can correctly assess which queries require review by a live human. After training and testing, it can handle thousands of emails in 1 minute," says Jiří Havlíček, CEO of Daktela.

Employer playbook for deploying AI in the Czech Republic in 2025: start with fast, measurable wins - deploy voice conversational AI and intelligent triage to shave backlog and free agents for complex work, then expand into automated email triage and agent co‑pilots that surface suggested replies and case summaries.

Run pilots in a controlled sandbox and bake compliance into design: the Czech implementation plan and regulatory sandbox are already in place to speed testing under oversight (Czech AI Implementation Plan and Regulatory Sandbox - ÚNMZ).

Use intelligent triage and context panels to route, prioritise and surface macros so agents spend minutes - not hours - per case (Zendesk guide to intelligent triage and context panels), and apply voicebots, callbacks and self‑service flows for surge periods as recommended by conversational AI vendors to manage peak calls.

Anchor each project with data (CSAT, SLA, deflection rate), train agents in prompt design and exception handling, and keep a clear human “escape hatch.” Aim for practical scale - local deployments already show scale: MONETA's Czech voicebot “Tom” handles 1.5 million customers and reduced contact‑centre costs - so plan pilots that measure impact, iterate quickly, and document compliance and audit trails before full rollout.

“Our goal is to create a transparent and quality environment in the Czech Republic that will allow only trustworthy and competent entities to certify AI systems according to the rules of the European Act on Artificial Intelligence.”

Reduce replacement risk by turning irreplaceable human strengths into daily routines: become a Knowledge Curator who captures answers and edge‑case fixes so the data feeding bots actually improves (see the practical customer service upskilling guide for agents), master the “automation handoff” so transfers are seamless and customers don't feel bounced, and get fluent in prompt design and agent co‑pilot workflows so AI becomes an assistant not a competitor.

Train with realistic scenarios - including AI‑powered roleplay that simulates angry, technical or multi‑channel cases - to build empathy, stress management and decision autonomy under pressure (AI-powered roleplay customer service training ideas).

Push for microlearning, integrated coaching and performance feedback loops so improvements stick, and keep a few measurable goals (time‑to‑proficiency, CSAT, first‑contact resolution) to show the business your impact.

Remember the practical upside: bots can clear a backlog fast - Daktela's setup can train on past email traffic and “handle thousands of emails in 1 minute” - but that speed only wins when humans step in for nuance, persuasion and recovery; make those human skills your competitive moat (Daktela email bot survey on Czech customer preferences).

"We offer small and large businesses a free email analysis and AI bot setup to save them time in their daily routine. Our AI EmailBot will learn how to respond to what based on previous email communications over two days. It can correctly assess which queries require review by a live human. After training and testing, it can handle thousands of emails in 1 minute," says Jiří Havlíček, CEO of Daktela.

Policy choices are already reshaping how Czech companies and customer‑service teams will live with AI: the updated National Artificial Intelligence Strategy 2030 (approved July 24, 2024) doubles down on lifelong learning, VET modernisation and retraining pathways so frontline staff can shift into supervision, prompt design and exception handling, while national action plans and subsidy programmes (including a reported CZK 19 billion investment) aim to help SMEs adopt practical AI tools and co‑fund Digital Innovation Hubs; see the Czech AI Strategy overview for details and the 2019–2024 timeline of implementation.

Regulation is moving fast too - the EU AI Act entered into force on 1 August 2024, and Czech authorities are building sandboxes, testing environments and an auditable governance ladder so firms can trial customer‑facing systems under oversight.

The practical implication for the sector is clear: combine fast pilot projects with documented compliance, use EDIHs and Centres of Excellence to access tech and training, and treat reskilling as a budget line, not a footnote - otherwise the speed gains from automation will arrive without the human skills needed to steward them (Czech National AI Strategy timeline (Cedefop), Czech AI Strategy report (AI Watch)).

“According to our vision, the Czech Republic should be not only a user but also a creator of advanced artificial intelligence technologies.” - Jozef Síkela, Minister of Industry and Trade

Practical 2025 checklist for Czech companies and workers: run tight, measurable pilots (define KPIs like CSAT, SLA and deflection), then scale the winners while documenting compliance under the EU AI Act; test high‑risk systems in the new Czech regulatory sandbox to preserve innovation without legal surprise (ÚNMZ Czech AI implementation plan and regulatory sandbox); tap public funding and incubation (TWIST grants can fund projects up to CZK 30 million and the Ministry's calls are active) and partner with local EDIHs and Centres of Excellence to share tech and training (Czech National AI Strategy and EDIH guidance); update governance (map which models are Annex‑III/high‑risk, prepare conformity evidence and post‑market monitoring) and make a modest, visible investment in staff reskilling - practical courses that teach prompt craft and agent co‑pilot workflows shorten time‑to‑value (see Nucamp's AI Essentials for Work) (Nucamp AI Essentials for Work bootcamp).

A useful rule: aim for pilots that show a clear CZK benefit (a single grant or a documented efficiency gain can justify scaling) and keep a human “escape hatch” in every customer flow so trust scales with speed.

“Our goal is to create a transparent and quality environment in the Czech Republic that will allow only trustworthy and competent entities to certify AI systems according to the rules of the European Act on Artificial Intelligence.”