8.36%
2025 · enterprises with 10+ employed
COUNTRY · PL
Poland
Model development, business adoption and the research base behind them.
PL
2 catalogue entries
Broader Epoch catalogue, including variants; not a complete model census.
1.56% of GDP
All R&D, not AI-only investment.
What this model count includes
2Entries in the broader Epoch catalogue
0Entries with a notability criterion
Same source, year and developer-country attribution. The broader catalogue includes versions and sizes. Neither number is the total number of models developed here.
Models behind the count
Epoch · source snapshotLoading source records…
Beyond one catalogue
Selected projects checked against institutions and developers. These may overlap with Epoch; they are not added to its count.
PLLuMPL · Polish research consortium / Ministry of Digital Affairs
Adapted model familyMinistry documents development by Polish scientific institutions and language adaptation; this does not establish all variants as trained from scratch
Attribution sourceFirst-party checks reviewed 2026-10-25 · selected coverage
MODEL DEVELOPMENT
Poland in the model-building landscape
Annual notable-model entries · developer country · 2020–2025
International collaborations may appear in multiple countries. Counts are not additive market shares or a national AI-strength ranking.
Loading chartEpoch AI · CC BY 4.0 · Complete years through 2025 · incomplete 2026 excluded
AI IN BUSINESS · EUROSTAT
Source ↗AI adoption in Poland
Business adoption across Europe — and the divide between small and large firms
Adjust survey selection 2025 · All · 10+ persons employed
Poland · 20258.4%of surveyed enterprises use at least one AI technology
EU aggregate · same size class19.9%Regional aggregate, excluded from country ranking
Poland · businesses using AI · 2025
8.4% using AI
Loading chartAll · 10+ persons employed · Eurostat enterprise survey. The remainder is 100 minus the published adoption estimate. These are survey shares, not counts of respondents or measures of implementation depth.
The company-size divide · 2025
○ Small: 10–49 persons · ● Large: 250+ · percentage of enterprises within each size class. Each point has its own denominator.
Survey scope, dates and source flags
Percentage of enterprises using at least one AI technology. Selected non-financial business activities (NACE Rev. 2 C–J, L–N and 95.1). Enterprises with at least 10 persons employed. Not intensity of implementation, productivity impact or share of workers using AI.
Coverage is European survey participants, not a global adoption ranking. Small firms with fewer than 10 persons employed are excluded. Size classes and the total are separate survey populations; percentages must not be added. EU is an aggregate. Non-response, survey design and sector mix can affect comparisons.
Source flags are retained: b = break in time series; e = estimated; p = provisional; u = low reliability. Missing and confidential values are not replaced by zero. No 2022 observation is inferred.
Eurostat · isoc_eb_ai · source update 2026-06-15T11:00:00+0200 · captured 2026-10-23 · Eurostat reuse policy; attribution and stated exceptions apply
eurostat-enterprise-ai-size-v1 · SHA-256 f5f6d136c4ed04923d17a63c4b0b23d6999e7a4774450709ae214c24b7674357
The foundations around AI
These indicators describe all research and development, not AI-only expenditure or AI’s measured economic impact.
R&D expenditure
1.56% of GDP · all R&D · 2023 · Poland
Loading chartComparison uses 2023, the latest common year for this selection. The latest national observation above may be newer.
World Bank WDI / UNESCO Institute for Statistics · % of GDP · all R&DR&D researchers
3,675.06per million people · all R&D · 2023 · Poland
Loading chartComparison uses 2017, the latest common year for this selection. The latest national observation above may be newer.
World Bank WDI / UNESCO Institute for Statistics · per million people · all R&DEpoch AI · CC BY 4.0 · Model comparisons stop at 2025; incomplete 2026 is excluded. No forward-filled research observations.
Models connected to Poland
Epoch’s notable-model selection · developer country · international projects can appear in multiple countries
Fraternal dropout + AWD-LSTM 3-layer (WT2)Jagiellonian University,Mila - Quebec AI (originally Montreal Institute for Learning Algorithms),University of Montreal / Université de MontréalMoE-MultiJagiellonian University,Google Brain