The Complete Guide to Using AI as a Finance Professional in Czech Republic in 2025

For finance professionals in the Czech Republic in 2025, AI is fast moving from curiosity to core competence: the government's updated National AI Strategy (NAIS) and the EU AI Act are reshaping compliance and procurement expectations (see a clear regulatory overview at Global Legal Insights), while the Czech National Bank is already using LLMs and embeddings to improve inflation forecasting and nowcasting, a practical win for analysts who need faster, data‑rich signals (read the CNB pilot).

Market uptake - 41% of large firms use AI though only about 11% overall - plus funding programs like TWIST and OP TAK (multi‑hundred‑million‑koruna pipelines) create opportunities, even as export limits on advanced AI chips pose supply risks to big‑model projects.

With studies warning that over 2.3 million Czech jobs will need retraining, finance teams benefit from hands‑on training; the AI Essentials for Work 15-week syllabus offers a practical 15‑week path to learn prompts, tools and workplace use cases to stay compliant and competitive.

The regulatory landscape for AI in the Czech Republic now blends a clear national strategy with EU‑level rules: the updated National Artificial Intelligence Strategy 2030 (NAIS 2030), approved by Government Resolution No.

520 on 24 July 2024, sets seven priority pillars - from research and skills to legal, ethical and security aspects - and is being driven by the Ministry of Industry and Trade (see the Ministry's NAIS 2030 overview).

Implementation work focuses squarely on folding the EU AI Act (in force 1 August 2024) into national practice through an AI Implementation Plan that earmarks CZK 232 million for 2026–2028 to stand up enforcement, testing and support measures; practical steps include a regulatory sandbox and designation of market surveillance and conformity bodies (details in the White & Case AI Watch tracker).

For finance teams this means preparing for EU risk‑based obligations while navigating complementary Czech rules - GDPR/data protection, the Copyright Act's text‑and‑data‑mining provisions, cybersecurity and existing civil and consumer laws - and watching which national authorities (from the Czech Telecommunication Office to the Office for Technical Standardization) will take supervision and certification roles.

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

Compliance essentials for finance professionals in the Czech Republic in 2025 mean treating the EU AI Act as the de facto rulebook while folding in existing Czech law - GDPR/data protection, the Civil Code and the Copyright Act - plus sector rules such as DORA and MiCA for ICT resilience and crypto services; practical priorities include an up‑to‑date inventory of AI use, clear risk classification (credit scoring, AML monitoring and robo‑advisors are likely high‑risk), robust documentation of data quality and model decisions, mandated human oversight, vendor and third‑party ICT controls, and post‑market monitoring and registration where required.

Expect conformity assessments and sandboxes to be central to compliance: national implementation planning has earmarked funds and enforcement capacity, and Czech bodies (market surveillance, notifying authorities and a CSA‑run sandbox) will supervise testing and certification - think of a CZK 232 million implementation pot and a regulated sandbox where a fintech's credit‑scoring model must prove it won't discriminate before it goes live.

Start with tool classification, contractual ICT risk clauses, routine bias and explainability tests, and clear escalation paths to meet the heavy governance and documentation duties the literature expects; see the White & Case regulatory tracker and ARROWS' practical guide for fintech obligations for details and timelines.

“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.” - Jiří Kratochvíl, Chairman of the ÚNMZ

For Czech finance teams budgeting AI CapEx and writing procurement specs in 2025, U.S. export controls are an active supply‑risk that can suddenly reshape timelines and vendor economics: a January 2025 BIS “Framework for Artificial Intelligence Diffusion” introduced a three‑tiered cap/licensing regime for advanced AI chips and even new ECCNs for model weights, with many provisions slated for a May 15 compliance date (see the BIS interim rule explainer (Torres Trade Law, Jan 13, 2025)), while commentary and data analysis flagged the same restrictions as a driver of higher prices and supplier disruption (ITIF report on Nvidia's $5.5B impact).

Even after a May 13, 2025 rescission of certain diffusion rules, BIS continues to restrict access to the most advanced chips and the policy patchwork (FDPR, license exceptions AIA/ACM/LPP, country allocations) means procurement teams must bake export‑compliance checks, diversion risk clauses and longer lead times into RFPs, favour cloud or hosted compute options where licensing is centralised, and require suppliers to certify export authorisations; failing to do so can turn a planned GPU rack into a months‑long procurement black hole.

Practical next steps: insert export‑control warranty and audit rights in CapEx contracts, model tiered pricing for allocation risk, and track BIS/EU rule updates closely (read more on the three‑tiered limits analysis (ITIF) and the Finnegan rescission update (Finnegan LLP) for implementation nuances).

Funding and infrastructure in the Czech Republic are coming into sharp focus for finance teams looking to back AI projects: the MIT's TWIST programme is a headline source - grants can reach CZK 30 million per project as part of a CZK 5 billion envelope for 2025–2031 - and recent winners like Filuta AI show how grants translate into product advantages (Filuta's TWIST award aims to cut integration times from “one to two weeks” to “one to two days”), while OP TAK's digital calls have set aside earmarked funds (up to CZK 1.5 billion) for applied digital solutions and incubator pipelines continue to feed startups into the ecosystem.

Practical takeaways for finance professionals: structure budgets around phased co‑funding (TWIST covers up to 70% of eligible costs in many cases), model grants as non‑dilutive CapEx substitutes for cloud/compute, and link grant timelines to procurement and export‑control risk so GPU or hosted compute delays don't derail forecasts; local research centres and initiatives such as CLARA and expanded TREND‑successor funds also create opportunities for partnerships and talent‑rich collaborations that can cut time to value.

“The aim of the project is to create friendlier conditions for the use of the agents we have developed directly by clients. We want to reduce the high demands on the expertise of the people who will work with our solution and enable them to use autonomous planning agents completely independently.” - Filip Dvořák, Filuta AI

Enterprise adoption in the Czech Republic has moved from pilot to scale: AI use among Czech firms roughly tripled to about 40% in 2024, with 44% more expecting to implement it soon and nearly half of companies already flagging workforce impacts (see the Expats.cz coverage of AI adoption in the Czech Republic), and finance teams are squarely in the eye of this shift.

Recent surveys show finance leaders plan a rapid move into “agentic” workflows - only 6% currently use agentic AI but a further 38% intend to adopt within 12 months, pointing to roughly a sixfold jump in the next year (Wolters Kluwer) - and European benchmarking finds most deployments are strengthening back‑office functions (about 48% of live use cases) with document processing the single largest GenAI use (circa 66%), making tasks like contract review and KYC exponentially faster.

Practical, finance‑focused use cases gaining traction locally include FP&A augmentation, automated document summaries (imagine a 50‑page mortgage agreement distilled to the key covenants in seconds), semantic search for filings, smarter AML/KYC screening, and customer‑facing assistants; vendor and public programmes are lining up to help scale these pilots into production, with national DIHs and funding supporting lab‑to‑market work (see the EU AI Watch strategy note).

For CFOs and controllers the imperative is clear: prioritise data readiness, governance and phased rollouts so productivity gains - accuracy, time savings and faster scenario analysis - arrive without trading off compliance or explainability.

“At Wolters Kluwer, we are committed to continuous innovation for the office of the CFO. Last year, we launched the market's first AI-powered corporate performance management platform - the CCH Tagetik Intelligent Platform with Ask AI. We have evolved Ask AI to an embedded super agent; it now mobilizes cutting-edge agentic technology across multiple use cases, including responding to voice commands in multiple languages, drilling into data without the need for IT skills, and testing assumptions and running analysis. Agentic AI represents an evolutionary leap in how finance leaders operate.”

The Czech Republic's AI talent pipeline and startup scene are now a solid resource for finance teams: roughly 42 AI startups operate locally, with seven funded firms and three Series A+ players raising about $135M in total, so there's real supplier depth for document automation, KYC/AML and other finance use cases (see the Tracxn AI startups list for the Czech Republic).

Homegrown success stories range from Rossum's enterprise document‑processing play to Prague‑based Resistant AI fincrime detection, which markets fincrime detection that customers say drives 3x better fraud prevention, 5x faster review times and a 90% cut in manual reviews (see the Resistant AI company page), while university research projects such as OpenEuroLLM - coordinated by Charles University signal academic capacity to partner on open LLM work and skills development (see the Global Legal Insights analysis).

Incubators and the Technology Incubation project (178 supported projects, ~27% AI) further swell the talent pool, meaning finance leaders can prototype with specialist Czech vendors and tap research labs for production‑grade pilots that can cut weeks from rollout timelines and halve review backlogs overnight.

When hiring or working with AI contractors in the Czech Republic, the practical tax and hiring trade‑offs hinge on whether people are engaged as OSVČ (trade‑license freelancers) or through an s.r.o.

(limited liability company): freelancers register a živnost and must notify ČSSZ and their health insurer (registration can be quick, often days), but as an OSVČ they face mandatory social and health contributions - in 2025 a missed surprise for many is the minimum monthly social bill of CZK 4,759 and health insurance of CZK 3,143 - while an s.r.o.

separates personal liability and pays 21% corporate tax with dividends taxed at 15% (see the clear comparison at Pexpats). For short‑term AI projects consider vetted OSVČ contractors (they can invoice without payroll taxes) but plan for VAT rules (registration required if turnover exceeds CZK 2,000,000) and confirm whether a contractor's role is truly autonomous to avoid misclassification; for strategic, recurring AI work an s.r.o.

can look more professional and flexible on insurance/tax optimisation. Startups and finance teams should build contracting clauses that require proof of trade‑license or company status, export‑control and IP warranties for model weights, and align payment terms to the 2025 contribution calendar - step‑by‑step guides to opening a živnost and navigating primary vs.

secondary OSVČ status are available from KOVER and DoMyTax to keep compliance tidy and predictable.

For Czech finance teams that want predictable, auditable gains from GenAI, start with document‑heavy workflows and pick tools proven in local deployments: intelligent document processing (IDP) platforms such as Rossum marry deep learning extraction, a unified validation workflow and an explicit LLM roadmap (Rossum's platform and company story show a focus on scaling document automation) - a useful signal when RFPs ask for exception rates and GDPR‑safe data flows (Rossum intelligent document processing company overview).

Look for vendors with measurable automation (Rossum reports manual intervention in only about 10% of cases), real production experience with LLMs (Rossum's Aurora was deployed to Wolt's AP operations across the Czech Republic, Slovakia and Slovenia) and broad integrations so transactions don't get stuck moving between systems (Rossum automation product deep dive and interview - The Recursive).

Pair IDP with robust multilingual tooling - use a secure translator like DeepL for on‑the‑fly Czech↔English document translation and localized quality checks - and pilot on AP/AR to measure exception volume, SLA recovery and downstream reconciliation time.

Operational best practices: require clear data‑handling and encryption guarantees, sample audit trails for explainability, phased rollouts that lock in quick wins, and vendor SLAs for model updates and retraining; remember Rossum's mission‑level promise - to enable one person to process one million transactions a year - as the “so what” test for any procurement decision (DeepL Czech↔English secure document translation API).

“Rossum's computer vision, NLP, and proprietary AI engine are built for scale. It can extract accurate data at high input volume, which makes it a good fit for critical document use cases.”

Conclusion - finance teams in the Czech Republic should treat 2025 as a launchpad, not a waiting room: map every AI use case, classify likely high‑risk systems (credit scoring, AML, automated decisioning), and fast‑track vendor due diligence, export‑control clauses and data‑quality checks into procurement so projects don't stall on conformity or chip shortages; follow the national implementation plan and timelines closely (see the White & Case AI Watch tracker) and use the CSA regulatory sandbox and ÚNMZ conformity system to de‑risk pilots before scale.

With the EU AI Act's next set of GPAI obligations arriving in August 2025, start internal audits now, lock in human‑oversight rules and transparent documentation, and align budgets to grant windows and training - grants and sandboxes make phased co‑funding and hosted compute viable while teams upskill.

For practical, workplace training that covers prompts, tools and governance in 15 weeks, consider the AI Essentials for Work 15-week syllabus to speed adoption without trading compliance for 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.” - Jiří Kratochvíl, Chairman of the ÚNMZ