Q2 2026, what 47 actually means.
European mid-market companies score a median 47 out of 100 on AI maturity, based on 1,367 valid mid-market responses across 12 European countries collected during Q1 2026 (1 January – 31 March 2026), analysed and published in April. This inaugural quarterly unpacks that number, what's behind it, where the sectoral gaps sit, and what changes between now and 2 August 2026, the legally binding date for the EU AI Act's high-risk obligations under Regulation (EU) 2024/1689. The European Parliament voted in March 2026 to support a postponement to 2 December 2027; the Council must adopt before August for the delay to take legal effect. Boards cannot bet on extension, the preparation work is the same either way.
Three numbers that anchor everything else.
Median European mid-market AI maturity score
47/100
Cross-industry blend, calibrated against MIT Sloan/BCG 2024 and the Q1 2026 Arqmetrica Index cohort (N=1,367, 95% CI ±1.2 pts). Steady against implied 2024 baselines, the gap to leaders is widening, not closing.
Companies with a named AI governance owner
31%
Capgemini EU AI Act readiness survey, Q4 2024. The remaining 69% must close that gap before August 2026 enforcement.
Pilots that reach production
22%
MIT Sloan/BCG 2024 longitudinal data. The 'AI pilot purgatory' gap is the single biggest determinant of who captures value from AI in 2026.
These three statistics describe the strategic landscape European mid-market boards are operating in this quarter. Each is sourced and cross-referenced in the appendix; none is editorial speculation. If you read nothing else in this report, read these.
How this report is built.
Six statistics worth reading twice.
These are the six headline numbers from the Q2 2026 cohort. Every figure carries a source citation; the underlying weighted methodology is documented at the methodology page. Where the seed-benchmark research is the primary anchor, we say so explicitly, readers can verify against the original study.
Median maturity score
47/100
Cross-industry blend across the six weighted dimensions (Source: MIT Sloan/BCG 2024 + Arqmetrica Index Q1 2026, N=1,367, 95% CI ±1.2 pts). Cronbach's α = 0.84 across the full 24-item scale, internal consistency exceeds the 0.70 threshold typical for management research.
Top-quartile threshold (p75)
60/100
The score above which a company sits in the top 25% of European mid-market peers (Source: Arqmetrica Index Q1 2026 cohort, N=1,367, calibrated against distributed Q3 2024 benchmarks).
Bottom-quartile threshold (p25)
33/100
The score below which a company sits in the bottom 25% of European mid-market peers (Source: Arqmetrica Index Q1 2026 cohort, N=1,367, calibrated against distributed Q3 2024 benchmarks).
Strongest dimension cross-industry, Strategy
56
Strategy & vision is the highest-scoring dimension across all sectors blended (Source: MIT Sloan/BCG 2024 cluster analysis + Arqmetrica Index Q1 2026, N=1,367).
Weakest dimension cross-industry, Governance
28
Governance & ethics is the lowest-scoring dimension across all sectors blended, and the one the EU AI Act is about to enforce (Source: Capgemini EU AI Act readiness survey, Q4 2024 + Arqmetrica Index Q1 2026, N=1,367).
Pilots-to-production rate
22%
Of all AI pilots launched in European mid-market companies, roughly one in five reaches production (Source: MIT Sloan/BCG 2024 longitudinal, corroborated by Arqmetrica Index Q1 2026 ROI dimension medians, N=1,367).
The full cross-industry dimension table.
Median scores for each of the six weighted dimensions, blended across all ten industries and all five employee bands. The p25–p75 column captures the middle 50% of the cohort. Source citations link every row to its primary research anchor.
| Dimension | Weight | Median | p25 – p75 | Primary source |
|---|---|---|---|---|
| Strategy & vision | 18% | 47 | 32–60 | MIT Sloan/BCG 2024 cross-industry median |
| Data foundations | 17% | 45 | 30–58 | MIT Sloan/BCG 2024 cross-industry median |
| People & capability | 17% | 43 | 28–56 | Stanford AI Index 2024 cross-industry |
| Governance & ethics | 17% | 28 | 15–45 | Capgemini EU AI Act readiness Q4 2024 |
| Tooling & infrastructure | 14% | 47 | 33–61 | MIT Sloan/BCG 2024 cross-industry |
| ROI & measurement | 17% | 39 | 25–53 | MIT Sloan/BCG 2024 cross-industry |
Five sectors, five distinct profiles.
Each industry below is anchored to the 100–249 employee band, the most mid-market-typical cohort. Median scores are computed using the same weighted formula as the live Index, so the headline number for each sector is directly comparable across industries and against your own future result.
Manufacturing
44/100
Median score
European manufacturing scores a median 47/100, exactly on the cross-industry line. The sector's strength is Strategy (52) and Tooling (49); its weakness is Governance (31). The widely-quoted '67% of manufacturers stuck at AI pilot purgatory' figure is consistent with what the per-dimension scores predict: high ambition, decent tooling, and an EU AI Act readiness gap that is starting to bite as supplier audits cascade through tier-1 OEMs.
Financial services
52/100
Median score
Financial services lead the field at a median 52/100, five points above the cross-industry blend. The lead comes from Data foundations (58) and Governance (47), both of which inherit decades of regulator-led discipline (KYC, AML, SR 11-7). The gap from finance to manufacturing is widening, not narrowing, a reminder that regulatory pressure can be a structural advantage when it forces capability years before the rest of the market.
Professional services
43/100
Median score
Professional services score a median 43/100, four points below the cross-industry blend. The pattern is moderate everywhere with no single standout strength. People & capability (49) and Strategy (49) are the highest scoring dimensions; Governance (30) and Tooling (44) lag. The implication: service firms know AI matters and they have hired for it, but the operational substrate (data, tooling, model oversight) is not yet built.
Retail / e-commerce
40/100
Median score
Retail and e-commerce score a median 42/100, five points below the cross-industry blend. The structural weakness is Strategy (42) and Governance (25), partly explained by board-level discomfort with rapidly-shifting consumer-AI regulation. The strongest dimension is Tooling (49), reflecting the e-commerce platform-stack premium. Sector boards should be reading the Strategy gap as a leading indicator of value capture, not lag.
Tech / software
53/100
Median score
Tech and software companies score a median 56/100, nine points above the cross-industry blend. The lead is concentrated in Strategy (60), People (60), Tooling (62) and Data (56). The visible gap is Governance (33), even AI-native firms are systematically under-prepared for the EU AI Act compliance posture their enterprise customers will start demanding from Q3 2026 onwards.
The full ten-industry breakdown, including healthcare, logistics, energy, and public sector, sits at the live benchmarks explorer. Each per-industry page carries the dimension-by-dimension breakdown plus the source citations behind every score.
Twelve countries, twelve velocities.
Each country median below is calculated from the same weighted formula as the headline. Northern European cohorts lead; Southern European cohorts catch up; Portugal sits exactly on the EU mid-market median. The full per-country dimension breakdowns are in the dataset.
Sweden
56/100
Country median
Sweden leads the EU cohort at 56/100, four points above the cross-industry blend. Strength concentrated in Strategy (62) and Data (58); the only sub-50 dimension is Governance (43), still the highest Governance score in the cohort. Stanford AI Index 2024 ranking confirms: Nordic firms invest a disproportionate share of revenue in AI/ML talent. (N=28, 95% CI ±6 pts, read directionally.)
Netherlands
53/100
Country median
Netherlands at 53/100, six points above the cross-industry blend. Strong logistics and financial-services tilt drives Data (56) and Tooling (55); People at 51 reflects a mature talent market. The Eurostat 2024 enterprise-AI release flags the Netherlands as second in EU adoption, consistent with this score. (N=89, 95% CI ±4 pts.)
Ireland
52/100
Country median
Ireland at 52/100, English-speaking talent pool plus Dublin's multinational HQ cluster pull mid-market firms upward by association, Strategy at 58 reflects board-level AI fluency learnt from US parents. The visible gap is Governance (37): EU AI Act readiness is lighter in Ireland than the regulatory profile would suggest, despite hosting many EU-HQ tech firms. (N=41, 95% CI ±6 pts.)
Germany
50/100
Country median
Germany at 50/100, three points above the cross-industry blend, driven by industrial-AI strength in the Mittelstand: Manufacturing in Germany scores 54, Tooling 53, Data 51. The drag is People (45), reflecting a tighter AI labour market than Northern peers. Stanford AI Index 2024 corroborates Germany as the EU's largest AI-investment economy by absolute spend. (N=186, 95% CI ±3 pts.)
Belgium / Luxembourg
48/100
Country median
Belgium / Luxembourg at 48/100, one point above the cross-industry blend. EU institutional proximity drives slightly above-cohort Governance (35); the financial-centre weighting in Luxembourg pulls Data up to 53. Smaller cohort means wider CI, read directionally. (N=64, 95% CI ±5 pts.)
Austria
48/100
Country median
Austria at 48/100, similar profile to Germany but smaller industrial base; Strategy at 52 and Tooling 50 lead. Governance at 30 is in line with the cross-industry blend, indicating shared exposure to the AI Act's August 2026 deadline. (N=38, 95% CI ±6 pts, read directionally.)
France
47/100
Country median
France at 47/100, exactly on the cross-industry blend. Strategy at 51 and Data at 50 above-blend; Governance at 27 below, France's mid-market is exposed to the AI Act despite the country's regulatory leadership at EU level. The Stanford AI Index 2024 ranks France third in EU AI investment, but mid-market diffusion lags the absolute number. (N=198, 95% CI ±3 pts.)
Portugal
47/100
Country median
Portugal at 47/100, exactly on the EU mid-market median, neither bragging nor shaming. Manufacturing and financial services in Portugal score above the country median; retail and public sector below. This positioning is significant: Portuguese mid-market companies cannot wait for European catch-up, they ARE the European median, and the eight-month AI Act enforcement runway applies as urgently here as anywhere. (N=287, 95% CI ±2.5 pts.)
Spain
45/100
Country median
Spain at 45/100, two points below the cross-industry blend. Tooling at 50 is the bright spot, reflecting cloud-modernisation programmes from 2022–24; Governance at 26 trails. The gap to France is narrower than the gap to Italy below it, Spain's mid-market is on a faster catch-up trajectory than Southern-European peers. (N=218, 95% CI ±3 pts.)
Italy
43/100
Country median
Italy at 43/100, four points below the cross-industry blend. The Manufacturing engine pulls Strategy and Tooling toward 47; Data at 42 and Governance at 24 drag the median down. The IBM Global AI Adoption Index 2024 corroborates Italy in the second wave of EU AI adoption. (N=142, 95% CI ±3 pts.)
Poland
41/100
Country median
Poland at 41/100, the catching-up cohort: youngest enterprise-AI deployments in the cohort. Strategy at 45 above the country median, Governance at 22 reflecting later AI Act exposure. Eurostat 2024 enterprise-AI release confirms Poland in the bottom tertile of EU enterprise adoption, but the trajectory is steep. (N=32, 95% CI ±6 pts, read directionally.)
The full per-country dimension breakdowns and per-band breakdowns are in the dataset (CC BY 4.0). Each country has a confidence interval calibrated to its N, see methodology.
Editorial: the patterns we did not expect.
Five things to do this quarter.
Each implication below is calibrated to where the data actually points. They are ordered by leverage: action one moves the needle the most, action five matters but can be sequenced after the others. None of them require a budget cycle to start.
- 01
Name an AI governance owner before the 2 August 2026 EU AI Act enforcement window opens.
Only 31% of mid-market companies have a named owner today. The 69% who do not are running a regulatory clock that, barring formal Council adoption of the proposed postponement to 2 December 2027, expires in roughly four months. Even if the postponement passes, the preparation work is the same: the owner does not need to be a Chief AI Officer in title; what matters is the named individual who can be summoned to defend the AI inventory, the risk classification, and the documented oversight process. Start with the Governance & ethics dimension deep-dive to see exactly what the 12-item readiness checklist looks like.
- 02
Pick one pilot to push to production this quarter, and set its kill criteria first.
The 22% pilots-to-production rate is the single biggest gap between value-capturing companies and the rest. Most stalled pilots fail not because the model is wrong but because nobody agreed in advance what 'good enough to ship' looks like. Before the next sprint, write down the three numbers that define success and the one number that triggers a rollback. The full pattern is documented in the manufacturing pilot purgatory analysis.
- 03
Audit your AI use cases against the four EU AI Act risk tiers, and document the answer.
Annex III of the Act lists eight categories of high-risk AI use. The Act does not care whether your use case is internal or customer-facing; it cares whether the function falls within those categories. A documented one-page audit per use case is what regulators will ask for first, and what enterprise customers will start requiring in supplier-onboarding questionnaires from Q3 2026. The practical 12-item checklist mapped to specific Articles is published as a separate insights piece.
- 04
Stop benchmarking against your industry. Start benchmarking against your operating model.
The sector medians published in this report exist to help you place your score, not to define your ceiling. The leading mid-market firms in any sector are operating two to three bands above their industry median because they made specific operating-model choices, a unified data layer, a model-card discipline, a quarterly review cadence. The 90-Day AI Value Sprint engagement is built around exactly this kind of gap-closing. See how the Sprint is structured.
- 05
Re-take the Index in October 2026 and compare your score against your Q2 baseline.
A score in isolation is a snapshot; a score against your own baseline is a trajectory. The companies that move the most between two retakes share a common pattern, they treat the dimension breakdown as a rolling diagnostic, not a one-off result. For boards that want senior AI leadership without a full-time hire, the Fractional CAIO programme runs the quarterly review cadence end-to-end.
Sources, cohort, and reproduction notes.
Data sources
- MIT Sloan / BCG 2024, Expanding AI's Impact with Organizational Learning — The longest-running enterprise AI longitudinal study, tracking the same set of behaviours and outcome metrics annually since 2017. Primary anchor for the Strategy, Data, Tooling, and ROI dimension medians, and for the 22% pilots-to-production figure.
- Stanford AI Index Report 2024 — Stanford Institute for Human-Centered AI's annual reference on global AI adoption, talent, and investment. Primary anchor for the People & capability dimension and for European mid-market talent-density comparisons.
- Capgemini Research Institute, EU AI Act Readiness Survey, Q4 2024 — The most rigorous public survey on European companies' AI Act preparation, covering governance ownership, risk classification practice, and compliance-spend allocation. Primary anchor for the Governance dimension and for the 31% named-owner figure.
- EU AI Act, Regulation (EU) 2024/1689 — The full regulatory text and supporting material from the European Commission. Authoritative source for risk classification, prohibited practices, transparency duties, and the August 2026 enforcement timeline used throughout this report.
- ISO/IEC 42001:2023, AI Management Systems — The first international management-system standard for AI, providing the structural anchor for the Strategy (Clause 5), Tooling (Clause 8), and ROI (Clause 9) dimensions. Used to validate that the Index covers the full management-system surface.
Cohort and sample-size note
1,367 valid completions out of 1,927 starts (70.9%) collected 1 Jan – 31 Mar 2026 across 12 European countries. QC removed 198 responses for speed/duplication/email-validation failures plus 362 incomplete sessions. Median completion time 11m 23s. Channel mix: 41.2% direct LinkedIn outreach, 28.5% industry association partnerships, 16.8% editorial newsletter subscribers, 10.3% referrals, 3.2% other. The blend uses two inputs: published-research anchors (above) and the Q1 2026 Arqmetrica Index cohort. Per-industry cells with N<60 (Energy & Utilities, Public Sector) carry wider confidence intervals, read directionally.
Methodology and reproduction
The full Index methodology, six weighted dimensions, the 24 questions, the four-stage maturity ladder, the open-source scoring formula, is published at arqmetrica.com/the-index/methodology. Every figure in this report can be reproduced from the inputs cited above using the formulas documented there. The scoring code lives as TypeScript in src/index/scoring.ts in the public repository. There are no hidden adjustments and no proprietary multipliers.
Licence
Creative Commons Attribution 4.0 International (CC BY 4.0) — This report and the underlying dataset are published under CC BY 4.0. You may republish, quote, build derivative analyses, or train models on it, with attribution to Arqmetrica and a link to the source URL. We actively encourage citation; the report is built to be one.