Building a Europe AI Can See: Czech Top Companies AI research

Key Takeaways

• No Czech company in this dataset reached Grade B or above. EP Group leads at 66, followed closely by ČEZ (65), Česká spořitelna (64), and O2 (64) – four companies bunched within two points of each other at the top of Grade C.
• The dataset splits exactly down the middle: 5 companies in Grade C, 5 in Grade D, with a national average of 55.3 – squarely on the C/D border, in line with Croatia (53.1) and well below Belgium’s stronger showing.
• Škoda Auto, the country’s best-known global export brand, posts the lowest score in this dataset (42, Grade D), driven by three competing H1 tags and a Depth score of just 44 – a surprising result for a company that sells cars in over 100 markets.
• Structural Decay affected 8 of 10 companies, split across three failure modes: fragmented intent from multiple H1 tags (Seznam.cz, Škoda Auto, Agrofert, ČSOB, Plzeňský Prazdroj – 5 companies), a missing H1 tag entirely (Komerční banka), and absent date signals (Česká spořitelna, O2).
• Czechia’s three largest domestic banks land in three different outcomes. Česká spořitelna leads the group at 64 (Grade C), ČSOB follows at 55 (Grade C), and Komerční banka trails at 47 (Grade D) – the only one of the three with no detectable H1 tag at all.
• Freshness does not reliably predict grade in this dataset, breaking a pattern this series documented cleanly in Croatia. Three of the five Grade C companies (Česká spořitelna, ČSOB, O2) scored a flat 0 on Freshness, while two Grade D companies (Agrofert, Plzeňský Prazdroj) posted real Freshness scores of 57 and 69.
• Schema is the deepest structural gap in the dataset, averaging just 35.8 across all ten companies. Agrofert scored the lowest at 10, meaning AI systems have almost nothing machine-readable to draw on when trying to identify the group’s structure or holdings.
• EP Group posts one of the top scores in the dataset yet is parsed by AI systems as being about “Home,” not about EP Group – the same generic-anchor failure mode this series first isolated in Croatia. ČEZ, by contrast, is correctly parsed as “Skupina ČEZ,” giving AI systems a direct, unambiguous entity anchor.

Building a Europe AI Can See (Research Series)

This article is part of the ongoing Building a Europe AI Can See research initiative, analyzing the AI visibility of Europe’s flagship companies using a consistent methodology.

This is the fifth installment in this series’ country-level strand, following Austria, Belgium, Croatia, and Cyprus, in the Building a Europe AI Can See series, the research hub tracking this project as it expands across the continent.

A Country Split Exactly Down the Middle

Seznam.cz. Škoda Auto. Skupina ČEZ. Agrofert. Česká spořitelna. ČSOB. EP Group. Komerční banka. O2. Plzeňský Prazdroj. Ten companies that between them define the Czech economy: its homegrown search engine and internet portal, its flagship automotive exporter and the country’s largest single employer, its national power and energy utility, its largest agriculture-to-media conglomerate, two of its three largest retail banks, a fast-growing energy and industrial holding group, its third major domestic bank, its dominant mobile and fixed-line operator, and the world’s oldest continuously operating lager brewery.

Where Croatia showed the widest spread this series has recorded at country level (33 points between its best and worst performer), Czechia shows something closer to a shared national ceiling with a long, uneven tail. Four companies cluster tightly between 64 and 66. The other six spread out below them, down to a low of 42. No company clears the 75-point threshold this framework treats as good-to-strong AI readiness, and none comes close.

Methodology

Each company’s primary corporate website was evaluated using the AI Visibility Inspector across four structural dimensions:

• Structure – how content is architecturally organized for machine parsing, including H1 clarity and navigational coherence
• Depth – the substantive quality and retrievability of content as AI systems process and extract it
• Schema – the presence of structured data markup that enables confident entity identification and citation
• Freshness – whether content age signals, specifically dateModified JSON-LD, are present and verifiable to AI retrieval systems

The overall AI Retrieval Index score runs from 0 to 100. Scores below 50 indicate significant structural invisibility (Grade D). Scores between 50 and 74 represent fair to moderate visibility with material gaps (Grade C). Scores at 75 and above indicate good to strong AI readiness (Grade B or higher).

A Structural Decay warning is triggered when critical signals are absent or conflicting: a missing H1 tag preventing AI parsers from anchoring a primary topic, multiple competing H1 tags fragmenting intent, or absent date signals leaving content age unverifiable.

The Scores

National average: 55.3 – Grade C/D border, AI Retrieval Index

Zero companies in Grade A. Zero in Grade B. Five in Grade C. Five in Grade D. Czechia’s best performer, EP Group at 66, would sit mid-table in the Croatian comparison and well behind Belgium’s leaders. Czechia’s worst performer, Škoda Auto at 42, is a notable result given the brand’s international recognition and export footprint.

Five Findings the Czech Corporate Sector Needs to See

Finding 1: A Clean 5–5 Split, Anchored by a Four-Way Tie at the Top

Unlike Croatia’s wide spread or Austria’s tight national ceiling, Czechia shows a distinctive shape: four companies – EP Group, ČEZ, Česká spořitelna, and O2 – packed within two points of each other at 64–66, followed by a six-point drop to ČSOB at 55, and then a long, uneven tail down to Škoda Auto at 42. The market has a clear upper tier, but nothing in it reaches Grade B, and half the dataset falls into Grade D.

Finding 2: Structural Decay Hit 8 of 10, Split Across Three Failure Modes

Eight of the ten companies evaluated triggered a Structural Decay warning – a higher rate than Croatia’s 7 of 10 and Belgium’s matching figure. The failures split unevenly across three patterns:

Fragmented intent from multiple H1 tags – the dominant failure mode in this dataset: Seznam.cz and Agrofert (2 H1 tags each), ČSOB and Plzeňský Prazdroj (2 H1 tags each), and Škoda Auto (3 H1 tags, the most of any company in this report).

Missing H1 tag entirely: Komerční banka, the only company in the dataset where AI parsers found no primary-topic anchor at all.

Absent date signals: Česká spořitelna and O2, both of which otherwise post two of the four strongest overall scores in the dataset – undone in the same way Zagrebačka banka and Atlantic Grupa were in Croatia’s report, by content whose age cannot be verified.

Only two companies, ČEZ and EP Group, triggered no Structural Decay warning at all – a smaller clean-baseline group than Croatia’s three out of ten, and a signal that even the best-performing Czech companies in this dataset have more structural work ahead of them than their scores alone suggest.

Finding 3: Škoda Auto’s Score Is the Standout Surprise in This Dataset

Škoda Auto is Czechia’s most globally recognized brand in this sample, selling vehicles across more than 100 markets as part of the Volkswagen Group. It posts the lowest score in this dataset: 42, Grade D, dragged down by three competing H1 tags and a Depth score of just 44 – the weakest Depth result of any company evaluated here. For a company competing directly against European and global automotive peers whose group-level digital infrastructure often carries mature structured-data standards elsewhere, the Czech-market homepage lags well behind what its parent group has already solved in other markets. This is a sequencing gap, not a resource gap – and it is the single most striking finding in this report given the brand’s international profile.

Finding 4: Three Domestic Banks, Three Different Outcomes

Česká spořitelna, ČSOB, and Komerční banka are three of Czechia’s largest retail banks, operating under comparable regulatory and disclosure obligations. Their AI Retrieval Index results diverge sharply: Česká spořitelna leads at 64 (Grade C), ČSOB follows at 55 (Grade C), and Komerční banka trails at 47 (Grade D) – the only one of the three to show no detectable H1 tag whatsoever, leaving AI parsers with no primary-topic anchor on its consumer-facing homepage. All three carry strong Depth scores (75–90), so the gap is not a content problem. It is a structural and schema problem, and Komerční banka’s Structural Decay warning is the more severe of the two failure types this dataset documents.

Finding 5: Freshness Stops Being a Reliable Predictor of Grade in Czechia

Croatia’s report identified Freshness as the cleanest single-dimension predictor of grade outcome this series had documented: every Grade C company scored above 60, every Grade D company scored a flat 0. Czechia breaks that pattern. Three of this dataset’s five Grade C companies – Česká spořitelna, ČSOB, and O2 – scored a flat 0 on Freshness and still cleared the Grade C threshold on the strength of Structure and Depth alone. Meanwhile two Grade D companies, Agrofert (57) and Plzeňský Prazdroj (69), carry real, verifiable Freshness signals but are held back by weak Schema scores (10 and 20, respectively). The lesson for the Czech dataset is that no single dimension dominates outcomes here – Structure, Depth, and Schema all carry enough weight to move a company across the grade boundary independent of Freshness.

What AI Actually Sees

The entity interpretation outputs surface the same failure mode this series first documented in Croatia: a company can post a strong score and a clean Structural Decay result and still fail at the most basic task of telling an AI system who it is.

EP Group, despite posting the highest score in this dataset and a perfect Structure result of 100, is parsed by AI systems as being about “Home” – not EP Group, not the company’s own name. The H1 tag exists, so no Structural Decay warning fires, but the page’s declared primary topic is the generic label of the page type rather than the company’s identity.

Skupina ČEZ shows the alternative. Its page is parsed as being about “Skupina ČEZ,” the company’s own name, giving AI systems a direct, unambiguous entity anchor to build on. The gap between “Home” and “Skupina ČEZ” is a handful of characters in a title tag or H1 – and it is the difference between a page that helps an AI system identify the company and one that leaves it to guess, regardless of how strong every other structural signal looks.

Komerční banka, missing a usable H1 altogether, returns no confident primary topic at all. For a retail bank whose customers and prospective customers increasingly route financial-product research through AI assistants, this means the system has no structural declaration of what the company fundamentally is, and has to reconstruct identity from secondary text – the least reliable and least authoritative path to entity recognition in this framework.

The Czech Paradox

None of these ten companies are digital startups improvising their content strategy. Škoda Auto operates inside the Volkswagen Group, one of the largest automotive groups in the world, with mature digital infrastructure already deployed across other group markets. Česká spořitelna and ČSOB operate as the Czech arms of Erste Group and KBC Group, respectively, two of Europe’s larger banking groups. ČEZ and EP Group operate substantial energy portfolios with corresponding public-disclosure obligations. Seznam.cz is the country’s own homegrown search and internet platform – the one company in this dataset whose entire business is built on understanding how machines parse the web, and it still posts a Grade D score with a fragmented-intent warning on its own homepage.

None of that institutional weight reliably predicts the AI Retrieval Index result. As in Croatia and Belgium, the gap documented here looks less like a resource constraint and more like a sequencing and localization gap: the Czech-market-facing website has not yet received the same machine-facing treatment as the group’s other digital properties, or, in Seznam’s case, has not yet turned its own search expertise inward on its own homepage structure.

The commercial stakes are direct. When a prospective car buyer asks an AI assistant to compare Škoda against its European peers, when a retail customer asks an AI system to compare Czech banks, when an investor asks what ČEZ or EP Group’s current energy strategy actually is, or when a job seeker asks what Agrofert’s businesses span, the answer is shaped by whichever source the system can retrieve, date, and confidently identify. Right now, in five of these ten cases, that confidence is compromised enough to land the company in Grade D, and in EP Group’s case, one of the strongest performers in the dataset is quietly undercut by a homepage that never gets around to naming the company at all.

Czechia’s flagship companies split cleanly down the middle. ČEZ and EP Group prove a clean structural baseline is achievable without heroic investment. Five others haven’t made it yet, and one of the country’s best-known global exports, Škoda Auto, posts the weakest score of any company evaluated in this report – a result worth sitting with given how far the brand’s reach already extends beyond Czech borders.

Research Date: August 2026 | Methodology: Ivica Srncevic Framework + AI Visibility Inspector. This research is independent, not sponsored by any organization or legal entity. All company names and logos are used for identification and analysis purposes only.