Data Analytics Statistics 2026
By Axis Intelligence Research
Co-author: Elena Rodriguez | Last updated: September 30, 2026 | License: CC BY 4.0
Only 39.85% of EU enterprises ran any data analytics in 2025, per Eurostat, even though 52.74% paid for cloud services. Axis Intelligence Research’s new Axis Data Conversion Index (ADCI) puts the average firm at 43.8 out of 100 — large enterprises score 80.0. The data stack is bought; the decisions aren’t being made on it.
Quick Answer
According to Eurostat’s 2025 enterprise ICT survey, 33.02% of EU enterprises perform data analytics with their own staff and 39.85% do so in-house or through a provider. In the United States, the Bureau of Labor Statistics counts 275,600 data scientists, projected to grow 35% by 2035. Axis Intelligence Research finds a 36.2-point conversion gap between large firms and the average business.
Key Findings
- Axis Intelligence Research finds the average EU enterprise scores 43.8 on the Axis Data Conversion Index (ADCI), versus 80.0 for large enterprises, as of Eurostat’s 2025 survey.
- Axis Intelligence Research finds 17.1% of EU enterprises doing data analytics rely only on external providers, with no in-house analytics staff (Eurostat 2025 data).
- Large EU enterprises are 2.83 times as likely as small ones to run analytics in-house (78.84% vs 27.86%), per Eurostat 2025.
- Axis Intelligence Research finds Denmark turns analytics into AI at 0.70 AI users per analytics user, more than double Poland’s 0.34 (Eurostat 2025).
- U.S. data scientists earned a $120,230 median wage in May 2025, 2.36 times the all-occupation median of $50,980, per BLS.
How Many Companies Use Data Analytics in 2026?
The most rigorous public answer comes from official statistics, not vendor surveys. Eurostat’s Digital economy and society statistics sample enterprises with 10+ employees across the EU using a harmonised questionnaire. Its latest release (data extracted January 2026, reference year 2025) is the figure set everyone else’s “percentage of companies using analytics” claim should trace back to.
According to Eurostat, 33.02% of EU enterprises performed data analytics using their own employees in 2025. A further group bought it in: 13.85% had analytics performed by an external organisation. Combined, 39.85% of EU enterprises did data analytics by either route.
Data analytics adoption by company size
| Segment (EU, 2025) | Analytics by own employees | Uses BI software | Uses AI | Uses paid cloud | Source |
|---|---|---|---|---|---|
| All enterprises (10+ staff) | 33.02% | 16.28% | 19.95% | 52.74% | Eurostat |
| Large (250+ staff) | 78.84% | 69.24% | 55.03% | 84.67% | Eurostat |
| Small (10–49 staff) | 27.86% | not published in release | 17.00% | not published in release | Eurostat |
Size is the single strongest predictor in the table. A large enterprise is 2.83 times as likely as a small one to have its own people doing analytics (78.84 ÷ 27.86), and 4.25 times as likely as the average enterprise to run business intelligence software (69.24 ÷ 16.28).
What data do companies actually analyze?
Transaction records dominate. Per Eurostat, 26.20% of EU enterprises analysed sales and payment records in 2025, 17.62% analysed customer data, 11.44% analysed social media data, and only 3.58% analysed satellite data.
| Data source analyzed (EU, 2025) | % of enterprises | Source |
|---|---|---|
| Transaction records (sales, payments) | 26.20% | Eurostat |
| Customer data | 17.62% | Eurostat |
| Social media data | 11.44% | Eurostat |
| Satellite data | 3.58% | Eurostat |
Elena Rodriguez’s read: Look at the order. Ledger data first, customer data a distant second. That’s the analytics program most companies actually run: a finance-owned revenue dashboard, refreshed monthly, sitting on top of the ERP. Nothing wrong with it, but it isn’t the customer-360 deck the platform vendor sold. When a BI rollout is scoped for 400 seats and the real consumers are the controller’s team, the per-seat math quietly doubles.
What Is the Axis Data Conversion Index (ADCI)?
The Axis Data Conversion Index (ADCI) measures how much of a business population’s cloud footprint shows up as decision-layer capability — in-house analytics, business intelligence software and AI — on a 0–100 scale. A score of 100 would mean decision-layer tools are as widespread as the paid cloud they typically run on.
Axis Intelligence Research built the ADCI because adoption statistics are usually quoted one at a time — “52.74% use cloud,” “19.95% use AI” — which hides the question buyers and investors actually ask: once the infrastructure is paid for, is anyone turning it into decisions?
ADCI formula and inputs
ADCI = [(in-house analytics % + BI software % + AI %) ÷ 3] ÷ paid cloud % × 100
All four inputs come from the same Eurostat 2025 enterprise survey, same population, same reference year, so they can be combined without mixing methodologies.
| Segment | In-house analytics | BI software | AI | Paid cloud | Calculation | ADCI |
|---|---|---|---|---|---|---|
| All EU enterprises | 33.02 | 16.28 | 19.95 | 52.74 | (69.25 ÷ 3) ÷ 52.74 × 100 | 43.8 |
| Large EU enterprises | 78.84 | 69.24 | 55.03 | 84.67 | (203.11 ÷ 3) ÷ 84.67 × 100 | 80.0 |
| Gap (large minus all) | 80.0 − 43.8 | 36.2 |
Source: Axis Intelligence Research calculation on Eurostat 2025 data (isoc_eb_das, isoc_eb_iip, isoc_eb_ai, isoc_cicce_use). Readings as of the 2025 reference year. This is the baseline reading.
How to read it: the typical EU business with 10+ employees converts under half of its cloud footprint into analytics capability; the large enterprise converts four-fifths. The ADCI compares how common each capability is across the population. It does not track whether the same firm holds all four, which Eurostat’s published aggregates don’t allow.
Elena Rodriguez’s read: An ADCI of 43.8 is the number a CFO should see before renewing a data-warehouse commit. It says the company is paying the storage-and-compute line but only partly running the insight line on top of it. The consumption meter runs either way. The fix is rarely another tool; it’s a named owner for the reporting layer and a budget line for the people who build it.
Do Companies Build or Buy Their Analytics?
Most build. But a meaningful minority buys the whole thing.
Axis Intelligence Research subtracted Eurostat’s in-house figure from its combined figure: 39.85% − 33.02% = 6.83 percentage points of EU enterprises do analytics only through an external provider. Divided by the 39.85% of analytics-active firms, that means 17.1% of analytics-active EU enterprises have no in-house analytics staff at all.
That segment is the addressable market for managed analytics, fractional data teams and BI-as-a-service. It is also the segment most exposed when a provider relationship ends: the dashboards leave with the contract.
Which Countries Lead in Data Analytics Adoption?
According to Eurostat’s 2025 data, Denmark leads the EU with 59.99% of enterprises performing data analytics in-house or through a provider, followed by Estonia (55.99%), the Netherlands (55.96%), Lithuania (54.11%) and Belgium (52.09%).
| Country | Analytics (own or external), 2025 | AI use, 2025 | AI-to-analytics ratio (Axis) | Source |
|---|---|---|---|---|
| Denmark | 59.99% | 42.03% | 0.70 | Eurostat |
| Estonia | 55.99% | — | — | Eurostat |
| Netherlands | 55.96% | — | — | Eurostat |
| Lithuania | 54.11% | — | — | Eurostat |
| Belgium | 52.09% | 34.54% | 0.66 | Eurostat |
| Bulgaria | 27.05% | 8.55% | 0.32 | Eurostat |
| Austria | 26.34% | — | — | Eurostat |
| Poland | 24.50% | 8.36% | 0.34 | Eurostat |
“—” = the country was not among those Eurostat named for AI in its 2025 release; we don’t estimate. AI-to-analytics ratio = AI % ÷ analytics %, Axis Intelligence Research calculation.
The spread between the leader and the laggard is 2.45 times (59.99 ÷ 24.50). The more telling number is the AI-to-analytics ratio. Denmark and Belgium have roughly two AI users for every three analytics users; Bulgaria and Poland have one for every three. Countries with an analytics base appear to convert it into AI at twice the rate, which argues that analytics maturity is the on-ramp to AI adoption, not a parallel track.
Austria is the outlier worth flagging: a high-income economy at 26.34%, next to Bulgaria rather than its neighbours. Eurostat’s release doesn’t explain it, and we won’t guess.
How far is Europe from its 2030 target?
The EU’s Digital Decade programme sets a target that at least 75% of enterprises use cloud computing, data analytics or AI by 2030, according to Eurostat. Because the target counts any of the three, analytics alone (39.85%) doesn’t measure progress against it. It does show that analytics is the lagging leg of the three-part target.
Why Do Companies Fail to Move From Analytics to AI?
Skills, not software. Among EU enterprises that considered AI but didn’t adopt it, Eurostat reports 70.89% cited a lack of relevant expertise, 52.52% cited unclear legal consequences, and 48.83% cited data-protection concerns. Only 20.68% said AI wasn’t useful.
| Reason for not adopting AI (EU, 2025) | % of enterprises that considered AI | Source |
|---|---|---|
| Lack of relevant expertise | 70.89% | Eurostat |
| Lack of clarity about legal consequences | 52.52% | Eurostat |
| Data protection and privacy concerns | 48.83% | Eurostat |
| Not considered useful | 20.68% | Eurostat |
EU AI use itself rose 6.47 percentage points in a year to reach 19.95% in 2025, per Eurostat. Demand isn’t the constraint; the bench is.
Elena Rodriguez’s read: “We lack expertise” at 70.89% is a hiring problem wearing a technology costume. It also explains the 17.1% outsourced-only segment: when you can’t staff the function, you rent it. Vendors pitching self-serve AI to this group should price in the implementation partner, because the buyer will have to.
How Many Data Scientists Are There, and What Do They Earn?
The skills gap has a price, and the U.S. labor market publishes it. According to the U.S. Bureau of Labor Statistics Occupational Outlook Handbook, data scientists held 275,600 jobs in 2025, with employment projected to reach 371,000 by 2035 — growth of 35%, against 3% for all occupations.
Data scientist salary by industry
| Metric / industry (U.S.) | Value | As of | Source |
|---|---|---|---|
| Median annual wage, all data scientists | $120,230 | May 2025 | BLS |
| Lowest 10% earned less than | $67,240 | May 2025 | BLS |
| Highest 10% earned more than | $199,130 | May 2025 | BLS |
| Publishing, broadcasting and content providers | $142,240 | May 2025 | BLS |
| Computer systems design | $132,380 | May 2025 | BLS |
| Credit intermediation | $129,490 | May 2025 | BLS |
| Management of companies | $128,050 | May 2025 | BLS |
| Insurance carriers | $108,650 | May 2025 | BLS |
Data scientist vs other analytics roles
On the same BLS page, adjacent analytics occupations earn less: mathematicians and statisticians $105,720, operations research analysts $88,940, and market research analysts $78,760 (May 2025 medians).
Where do data scientist job openings come from?
BLS projects about 24,800 openings a year over 2025–2035. Axis Intelligence Research ran the numbers: that is 9.0% of the 2025 workforce reopening every year (24,800 ÷ 275,600), and new growth (95,400 jobs) accounts for only 38.5% of the decade’s roughly 248,000 openings (95,400 ÷ 248,000). The other 61.5% are replacement demand — people moving roles or leaving the field. For hiring managers, that means the market is churning more than it is expanding.
How Fast Is Data Platform Spending Growing?
Public-company filings give the cleanest real-time read on analytics consumption. Snowflake, whose revenue is billed on consumption rather than seats, reported product revenue of $1,491.9 million for its fiscal second quarter ended July 31, 2026, up 37% year over year, per its company-reported results. Its net revenue retention rate was 126%, 828 customers generated over $1 million in trailing-12-month product revenue, and it guided fiscal 2027 product revenue to $6.07 billion.
These are company-reported figures from a single vendor, used here as a consumption signal, not as a market-size estimate.
Elena Rodriguez’s read: A 126% net revenue retention rate means the average existing customer spent 26% more than a year earlier. Put that next to an ADCI of 43.8 and the tension is obvious: the large, mature accounts are scaling consumption fast while the median European firm hasn’t built the reporting layer yet. The next leg of platform growth is the mid-market, and it will be sold with services attached.
Methodology
Collection. Axis Intelligence Research fetched every figure on September 30, 2026 from four primary documents: Eurostat’s Digital economy and society statistics – enterprises (data extracted January 2026), Eurostat’s Use of artificial intelligence in enterprises (data extracted December 2025), Eurostat’s Digital society statistics at regional level (Digital Decade target), the BLS Occupational Outlook Handbook: Data Scientists (last modified August 27, 2026), and Snowflake’s Q2 fiscal 2027 results release (September 2026). No figure comes from vendor surveys, aggregator pages or model memory.
Scope. Eurostat covers EU enterprises with 10+ employees and self-employed persons in NACE sections C–N (excluding K); the financial sector is outside the sample. BLS covers U.S. wage and salary employment in SOC 15-2051.
Axis calculations. ADCI = [(in-house analytics % + BI % + AI %) ÷ 3] ÷ paid cloud % × 100, equal weights, all inputs from the same Eurostat survey year. Outsourced-only share = (combined analytics % − in-house %) ÷ combined %. AI-to-analytics ratio = AI % ÷ analytics (own or external) % by country. Labor calculations: wage premium = data scientist median ÷ all-occupation median; openings share = annual openings ÷ 2025 employment; growth share = employment change ÷ (annual openings × 10). Every input and output is a row in the dataset, and the math can be re-run from it.
What the numbers don’t show. Eurostat publishes prevalences for the whole population, not firm-level overlaps, so the ADCI compares how widespread each capability is rather than tracking individual companies. Small-enterprise BI and cloud figures aren’t in the 2025 release, so no small-firm ADCI is published.
About This Dataset
The full fact table behind this page — 78 rows covering EU enterprise adoption of data analytics, BI, AI and cloud by size and country, U.S. data scientist employment and wages, Snowflake consumption metrics, and every Axis calculation with its formula — is available as data-analytics-statistics.csv under a CC BY 4.0 license.
Each row carries the source organisation, document, URL, retrieval date and a flag showing whether Axis calculated it. We update this page when new data changes the picture — a new Eurostat survey wave, a BLS projections revision, or a material shift in public data-platform results — not on a calendar.
Citation line: Axis Intelligence Research, Data Analytics Statistics 2026, 2026.
How to Cite This Page
APA: Axis Intelligence Research, & Rodriguez, E. (2026, September 30). Data analytics statistics 2026: Adoption, jobs, spend and the conversion gap. Axis Intelligence. https://axis-intelligence.com/data-analytics-statistics/
MLA: Axis Intelligence Research, and Elena Rodriguez. “Data Analytics Statistics 2026: Adoption, Jobs, Spend and the Conversion Gap.” Axis Intelligence, 30 Sept. 2026, axis-intelligence.com/data-analytics-statistics/.
Chicago: Axis Intelligence Research, and Elena Rodriguez. “Data Analytics Statistics 2026: Adoption, Jobs, Spend and the Conversion Gap.” Axis Intelligence, September 30, 2026. https://axis-intelligence.com/data-analytics-statistics/.
FAQ: Data Analytics Adoption, Talent and ROI
Is the typical company actually using the data platform it pays for?
Not fully. Axis Intelligence Research’s ADCI scores the average EU enterprise at 43.8 out of 100 in 2025, meaning in-house analytics, BI and AI are, on average, less than half as widespread as paid cloud services.
What share of small businesses do their own data analytics?
27.86% of EU enterprises with 10–49 employees performed data analytics with their own staff in 2025, according to Eurostat, compared with 78.84% of enterprises with 250+ employees.
Should a mid-sized company build an analytics team or outsource it?
Most analytics-active EU firms build: Axis Intelligence Research finds only 17.1% rely solely on external providers (Eurostat 2025). Outsourcing fits when volume is low; it concentrates risk if the provider owns the models and dashboards.
What is the biggest barrier to moving from analytics to AI?
Expertise. Among EU enterprises that considered AI but didn’t adopt it, 70.89% cited a lack of relevant expertise in 2025, per Eurostat — ahead of legal uncertainty (52.52%) and data-protection concerns (48.83%).
Which industry pays data scientists the most?
Publishing, broadcasting and content providers, with a median of $142,240 in May 2025, according to BLS, followed by computer systems design at $132,380.
Is data science still a growing career in 2026?
Yes. BLS projects data scientist employment to grow 35% from 2025 to 2035, from 275,600 to 371,000 jobs, with about 24,800 openings a year.
Which data do most companies analyze first?
Transaction records. 26.20% of EU enterprises analysed sales and payment data in 2025, per Eurostat, versus 17.62% analysing customer data.
Which EU country has the most analytics-driven businesses?
Denmark, where 59.99% of enterprises performed data analytics in 2025 per Eurostat, and where AI adoption (42.03%) is also the EU’s highest.
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