Women in Tech Statistics 2026
By Axis Intelligence Research
Co-author: David Park, Careers & Compensation | Last updated: September 22, 2026 | License: CC BY 4.0
Women hold 27.5% of the 6.71 million US computer and mathematical jobs and earn $1,828 a week against men’s $2,138. Combine both halves into one number and US computing sits at 49.9 on the Technology Parity Gap Index — Axis Intelligence Research’s measure of how far the field is from proportional representation at equal pay. Half of parity, as of 2025 annual averages.
Quick Answer
Women are 27.5% of US computer and mathematical occupations (BLS, 2025 annual averages) and 19.5% of EU ICT specialists (Eurostat, 2025). Women in US computing earn 85.5 cents for every dollar men in the same occupational group earn. Axis Intelligence Research’s Technology Parity Gap Index (TPGI) folds representation and pay into a single 0–100 reading where 100 is full parity: US computing scores 49.9, and only one of the nine computing occupations with complete BLS data clears 90.
Key Findings
- Axis Intelligence Research puts the Technology Parity Gap Index for US computer and mathematical occupations at 49.9 as of 2025 — women’s share of those jobs is 0.58 of their share of total employment, multiplied by a pay ratio of 0.855.
- Software developers post the strongest pay parity in US computing and among the weakest representation: women earn 94.5% of men’s median weekly pay in the occupation but hold only 20.3% of its 2.25 million jobs, for a TPGI of 40.7.
- Computer programmers record the lowest TPGI in the dataset at 25.9, driven by a pay ratio of 0.660 — women programmers’ median $1,406 a week against men’s $2,131.
- Women are 15.9% of US information security analysts, the lowest share of any named computing occupation BLS publishes, and ISC2’s March 2026 study puts women at 18% of US security teams.
- Axis Intelligence Research estimates the EU reaches ICT gender parity between 2093 and 2127 depending on method — projecting Eurostat’s 2015–2025 growth rates forward gives 2093; extending the observed +3.0 point-per-decade share gain linearly gives 2127.
What Percentage of Tech Workers Are Women in 2026?
The cleanest national answer comes from the Current Population Survey. In 2025 annual averages, 6,711,000 people worked in US computer and mathematical occupations, and 27.5% of them were women — against 47.1% of the 163.5 million-strong total US workforce. That ratio, 27.5 over 47.1, is the representation half of everything that follows.
The aggregate hides an unusually wide spread. Two computing occupations are majority-women. Several are effectively closed.
| Occupation | Employed (000s) | Women % | Source |
|---|---|---|---|
| Web and digital interface designers | 69 | 57.0 | BLS CPS Table 11, 2025 |
| Operations research analysts | 178 | 53.9 | BLS CPS Table 11, 2025 |
| Software QA analysts and testers | 72 | 50.6 | BLS CPS Table 11, 2025 |
| Computer systems analysts | 569 | 44.0 | BLS CPS Table 11, 2025 |
| Other mathematical science occupations | 486 | 41.8 | BLS CPS Table 11, 2025 |
| Web developers | 66 | 36.8 | BLS CPS Table 11, 2025 |
| Database administrators and architects | 148 | 36.3 | BLS CPS Table 11, 2025 |
| Statisticians | 50 | 32.8 | BLS CPS Table 11, 2025 |
| Computer support specialists | 677 | 29.1 | BLS CPS Table 11, 2025 |
| Computer and mathematical occupations (all) | 6,711 | 27.5 | BLS CPS Table 11, 2025 |
| Computer occupations, all other | 1,181 | 26.0 | BLS CPS Table 11, 2025 |
| Computer and information systems managers | 646 | 25.1 | BLS CPS Table 11, 2025 |
| Computer hardware engineers | 94 | 22.5 | BLS CPS Table 11, 2025 |
| Software developers | 2,254 | 20.3 | BLS CPS Table 11, 2025 |
| Computer programmers | 381 | 18.5 | BLS CPS Table 11, 2025 |
| Network and computer systems administrators | 154 | 18.2 | BLS CPS Table 11, 2025 |
| Information security analysts | 261 | 15.9 | BLS CPS Table 11, 2025 |
| Computer network architects | 96 | 8.0 | BLS CPS Table 11, 2025 |
Read the headcount column alongside the percentage and the shape of the problem changes. The three occupations at or above 50% women employ 319,000 people between them. Software developers alone employ 2.25 million at 20.3%. A field can look like it is diversifying at the level of job titles while the jobs that actually absorb the workforce barely move.
David Park: The comp bands explain part of this and nobody says it out loud. QA testing and interface design are the two rungs where women cross 50%, and they are also the two rungs with the shortest ladder above them. Software development is where the requisitions are, where the bands top out, and where the share sits at one in five. When a field’s representation is highest exactly where its compensation is lowest, “women in tech is improving” and “the money hasn’t moved” are both true statements about the same dataset.
How Much Less Do Women in Tech Earn? The Pay Gap by Occupation
BLS publishes median weekly earnings for full-time wage and salary workers by detailed occupation and sex, which gives the second half of the picture. Across all US computer and mathematical occupations, women’s median is $1,828 a week and men’s is $2,138 — a ratio of 0.855, or 85.5 cents on the dollar. That is above the all-occupations ratio of 0.821 ($1,089 against $1,326), so computing pays women better relative to men than the wider economy does. It is not a small distinction, and it is not parity.
| Occupation | Women $/week | Men $/week | Ratio | Source |
|---|---|---|---|---|
| Software developers | 2,383 | 2,523 | 0.945 | BLS CPS Table 39, 2025 |
| Computer support specialists | 1,348 | 1,452 | 0.928 | BLS CPS Table 39, 2025 |
| Operations research analysts | 1,573 | 1,819 | 0.865 | BLS CPS Table 39, 2025 |
| Computer and information systems managers | 2,305 | 2,691 | 0.857 | BLS CPS Table 39, 2025 |
| Computer systems analysts | 1,658 | 1,947 | 0.852 | BLS CPS Table 39, 2025 |
| Computer and mathematical occupations (all) | 1,828 | 2,138 | 0.855 | BLS CPS Table 39, 2025 |
| Computer occupations, all other | 1,507 | 1,791 | 0.841 | BLS CPS Table 39, 2025 |
| Other mathematical science occupations | 1,844 | 2,279 | 0.809 | BLS CPS Table 39, 2025 |
| Computer programmers | 1,406 | 2,131 | 0.660 | BLS CPS Table 39, 2025 |
| Information security analysts | not published | 2,255 | — | BLS CPS Table 39, 2025 |
Two rows deserve attention before anyone quotes the rest.
The computer programmer ratio of 0.660 is the widest gap in US computing and rests on 67,000 women — a small cell by CPS standards, and one where year-to-year movement should be expected. Programmer headcount has been shrinking for years as the title is absorbed into software development, and shrinking occupations tend to leave behind unusual seniority mixes. The figure is real and published; it is also the row a careful analyst hedges rather than leads with.
Information security analysts is the more instructive omission. BLS publishes men’s median at $2,255 and the occupational median at $2,287, but women’s median is suppressed — only 33,000 women in the occupation work full-time year-round, below the threshold at which BLS will publish. That is not a data gap to paper over. An occupation reaches the point where a federal statistical agency cannot publish a women’s wage because there are not enough women in it, and that fact is itself the finding.
The Technology Parity Gap Index (TPGI): One Number for Representation and Pay
Representation figures and pay-gap figures are almost always published separately, which lets an organization score well on one while failing the other and lets advocates and skeptics each cite the half that suits them. The Technology Parity Gap Index (TPGI) is Axis Intelligence Research’s attempt to close that loophole with a single reproducible reading.
TPGI formula and inputs
TPGI = (women’s share of the occupation ÷ women’s share of total employment) × (women’s median weekly earnings ÷ men’s median weekly earnings) × 100
Both inputs come from published BLS annual averages. The representation baseline is 47.1% — women’s share of all US employed persons aged 16 and over in 2025 — so an occupation that mirrors the national workforce scores 1.00 on the first term. The pay term is the ratio of medians for full-time wage and salary workers. A TPGI of 100 means an occupation employs women in proportion to their presence in the workforce and pays them the same median as men.
Worked example, computer and mathematical occupations: 27.5 ÷ 47.1 = 0.5839. 1,828 ÷ 2,138 = 0.8550. 0.5839 × 0.8550 × 100 = 49.9.
TPGI readings, US computing occupations, 2025
| Occupation | Representation ratio | Pay ratio | TPGI |
|---|---|---|---|
| Operations research analysts | 1.144 | 0.865 | 99.0 |
| Computer systems analysts | 0.934 | 0.852 | 79.6 |
| Other mathematical science occupations | 0.887 | 0.809 | 71.8 |
| Computer support specialists | 0.618 | 0.928 | 57.4 |
| Computer and mathematical occupations (all) | 0.584 | 0.855 | 49.9 |
| Computer occupations, all other | 0.552 | 0.841 | 46.4 |
| Computer and information systems managers | 0.533 | 0.857 | 45.6 |
| Software developers | 0.431 | 0.945 | 40.7 |
| Computer programmers | 0.393 | 0.660 | 25.9 |
| Information security analysts | 0.338 | not computable | NA |
Source: Axis Intelligence Research, computed from BLS CPS Annual Averages Tables 11 and 39, 2025. Baseline reading.
What the index surfaces that neither input surfaces alone: the two occupations with the best pay parity in US computing — software developers at 0.945 and support specialists at 0.928 — score 40.7 and 57.4, because near-equal pay applied to a small minority still produces a small total. Operations research analysts reach 99.0 the other way round, carrying a below-average pay ratio on the strength of being the one computing occupation where women outnumber their share of the national workforce.
The practical reading for anyone running a technology organization: equal pay audits, which is where most budgets go, move the term that is already closest to 1.00 in the roles that matter most. Pipeline and retention move the term sitting at 0.43.
What TPGI does and does not measure
TPGI is an occupational measure built on national medians. It does not adjust for tenure, seniority mix, firm size, metro, or hours beyond the full-time screen, and a median comparison will reflect differences in the distribution of women and men across levels within an occupation. That is deliberate: TPGI measures the outcome an economy produces, not the residual after controlling for the mechanisms that produce it. Where BLS suppresses a women’s earnings cell, the reading is reported as NA rather than estimated. This is the index’s first published reading and serves as its baseline; subsequent readings will follow each January release of CPS annual averages.
Women in Computer Science Degrees: Is the Pipeline Actually the Problem?
“Fix the pipeline” is the reflexive answer, so it is worth checking whether the pipeline and the payroll actually disagree.
Women earned 23.0% of US computer and information sciences bachelor’s degrees in 2023, according to the National Center for Science and Engineering Statistics in Science and Engineering Indicators 2026. Across levels: 23.1% of associate’s, 23.0% of bachelor’s, 34.0% of master’s, and 25.6% of doctorates. Total bachelor’s production in the field more than doubled over the decade, from 52,000 in 2013 to 114,000 in 2023.
At PhD-granting departments, the Computing Research Association’s Taulbee Survey reports women at 22.8% of CS bachelor’s degrees, 28.7% of CS master’s degrees and 24.5% of CS doctorates in 2023–24, with CS bachelor’s enrollment 23.8% women. The 2025 Taulbee cycle recorded a record 41,858 CS bachelor’s degrees alongside new majors falling to 33,490, down 13% across the longitudinal cohort — the first clear contraction in the incoming pipeline in years.
Now put the two datasets side by side. Women take 23.0% of computing bachelor’s degrees and hold 27.5% of computer and mathematical jobs. They take 23.0% of those degrees and hold 20.3% of software developer jobs. Neither comparison shows the collapse the pipeline narrative implies: the aggregate conversion is mildly positive, the software-specific conversion mildly negative, and both sit within a few points of the degree share.
David Park: This is the part that reframes the budget conversation. If degree share and job share were 23% and 12%, the attrition story would be doing the heavy lifting and retention spending would be the obvious lever. They are 23% and 27.5%. The workforce is not leaking women faster than the universities supply them — it is reproducing the supply almost exactly. That makes the binding constraint upstream of the first requisition, and it means an employer running an internal retention program is optimizing a term that is already near 1.0 while the input stays fixed at roughly one in four.
One place the leak is real is seniority. Taulbee’s faculty tables show women at 29.1% of assistant professors, 23.2% of associate professors and 19.0% of full professors in computing departments, with 28.1% of new tenure-track hires going to women. That is the shape of a cohort effect, an attrition gradient, or both — and it is the clearest published evidence of level-by-level thinning anywhere in the field’s public data.
Women in Cybersecurity and AI: The Two Fastest-Growing Specialisms
Security is where US computing’s representation figure bottoms out. Women are 15.9% of US information security analysts (BLS, 2025) across an occupation of 261,000. ISC2’s Women in Cybersecurity Study, published March 9, 2026, reports practitioners estimating women at 18% of US security teams and finds “little perceived change in the representation of women working in cybersecurity teams in the last two years.”
The country spread in that study is narrow and does not follow the usual development gradient:
| Market | Women on security teams | Source |
|---|---|---|
| India | 23% | ISC2, March 2026 |
| Canada | 21% | ISC2, March 2026 |
| United States | 18% | ISC2, March 2026 |
| China | 18% | ISC2, March 2026 |
| United Kingdom | 17% | ISC2, March 2026 |
| Japan | 16% | ISC2, March 2026 |
| Germany | 15% | ISC2, March 2026 |
| Netherlands | 15% | ISC2, March 2026 |
Two of the study’s findings cut against the standard framing. Women in cybersecurity are more likely than men to report significant AI knowledge — 27% against 17% — and equally more likely to have considered a career change to prepare for an AI-driven future, also 27% against 17%. Meanwhile 72% of women see the field as welcoming to women, against 77% of men; and 45% of women name work-life balance as their top challenge, against 29% of men.
The AI-skills result is worth stating plainly because it is the opposite of what most commentary assumes. The gap in security is not a readiness gap at the individual level. It is a distribution gap, and the same population reporting higher AI fluency is also the one most actively considering leaving.
Women in Tech by Country: The EU and the Parity Horizon
Eurostat’s ICT specialists series, extracted April 2026, is the best cross-country comparison available. More than 10 million people worked as ICT specialists in the EU in 2025, 5.0% of total employment, and 19.5% of them were women — up from 16.5% in 2015.
| Country | Women, % of ICT specialists | Source |
|---|---|---|
| North Macedonia | 31.7 | Eurostat, 2025 |
| Romania | 27.6 | Eurostat, 2025 |
| Latvia | 25.9 | Eurostat, 2025 |
| Norway | 22.9 | Eurostat, 2025 |
| Luxembourg | 20.0 | Eurostat, 2025 |
| European Union | 19.5 | Eurostat, 2025 |
| Switzerland | 17.4 | Eurostat, 2025 |
| Slovakia | 15.5 | Eurostat, 2025 |
| Hungary | 15.0 | Eurostat, 2025 |
| Czechia | 12.9 | Eurostat, 2025 |
In absolute terms Germany employs the most women ICT specialists at 436,800, followed by France (279,700), Spain (206,800), Italy (150,500), the Netherlands (138,600), Poland (129,100) and Sweden (115,700).
The EU ICT Parity Horizon
Women’s ICT employment in the EU grew at 6.6% a year between 2015 and 2025 against 4.4% for men — an 89.1% increase in women versus 53.5% in men. Women are entering European ICT half again as fast as men. The shares still moved only 3.0 points in ten years, because the base is so unequal that faster growth on a small number closes the gap slowly.
Axis Intelligence Research projects two dates from Eurostat’s own figures:
- Growth-rate method — parity in 2093. Hold the 2015–2025 rates and solve for the crossover: t = ln(80.5 ÷ 19.5) ÷ ln(1.066 ÷ 1.044) = 68.0 years from 2025.
- Linear method — parity in 2127. Extend the observed +3.0 point-per-decade share gain: (50 − 19.5) ÷ 0.3 = 101.7 years from 2025.
Both are projections of current rates, not forecasts, and each carries the flaw of its method: the growth-rate projection assumes a differential that has no obvious reason to persist for seven decades, and the linear projection ignores that the differential exists at all. Published together they bracket the honest answer — on the trajectory Europe has actually recorded, ICT gender parity is a next-century event, and the EU’s own Digital Decade target of 20 million ICT specialists by 2030 with “greater convergence of gender balance” contains no mechanism that changes either date.
For contrast, the countries moving fastest are not the ones with the largest sectors. Luxembourg’s women’s share rose 6.3 points in the decade, from 13.7% to 20.0%, with Sweden and the Netherlands each up 5.7. Bulgaria, Latvia and Cyprus moved the other way.
Methodology
Collection. Every figure in this report was retrieved from a primary source on September 22, 2026 and logged with its URL and retrieval date in the accompanying dataset. Sources: BLS Current Population Survey Annual Averages Tables 11 and 39 (2025 annual averages, published 2026); Eurostat ICT specialists in employment (isoc_sks_itspt, isoc_sks_itsps; data extracted April 2026); NCSES Science and Engineering Indicators 2026 (NSB-2026-1); CRA Taulbee Survey 2024 Annual Report and the 2025 Taulbee findings; ISC2 Women in Cybersecurity Study (March 9, 2026). No figure in this report is sourced from a secondary aggregator.
Derived country shares. Eurostat publishes several distributions as men’s shares. Where this report states a women’s share for Latvia, Czechia, Hungary, Slovakia, Norway, Switzerland or the EU 2015 figure, it is the arithmetic complement of the published men’s share, flagged in the dataset’s method_note column. The same applies to NCSES degree shares, published as men’s shares by level.
TPGI construction. TPGI = (women’s share of occupation ÷ 47.1) × (women’s median weekly earnings ÷ men’s median weekly earnings) × 100. The 47.1% baseline is women’s share of total US employment aged 16 and over, 2025 annual averages. The index is computed only where BLS publishes both a women’s and a men’s median for the occupation; where either is suppressed, the reading is NA. All nine computed readings and both component ratios ship in the dataset. A competent outsider can recompute every reading from the two BLS tables cited.
Parity horizon construction. The growth-rate projection solves for the year at which women’s and men’s EU ICT headcounts converge under the 2015–2025 average annual growth rates (6.6% and 4.4%), starting from the 2025 shares of 19.5% and 80.5%. The linear projection divides the remaining distance to 50% by the observed 0.3 percentage-point annual share gain. Both are stated as projections of observed rates.
Comparability. BLS occupational figures and Eurostat ICT specialist figures are built on different classifications — the US Standard Occupational Classification and ISCO-08 respectively — and the Eurostat definition includes electronic and telecommunication engineers, graphic and multimedia designers and ICT sales professionals, which the US computer and mathematical occupations group does not. The 27.5% and 19.5% figures are therefore reported side by side and are never averaged or merged. Eurostat also notes a 2021 break in the EU Labour Force Survey series and definitional differences in Spain and France.
On survey-based team estimates. ISC2’s country figures are practitioner estimates of team composition from a survey, not headcounts from administrative records, and are reported as such. They are shown alongside — never merged with — the BLS occupational figure for information security analysts.
About This Dataset
women-in-tech-statistics.csv is the fact table behind every number in this report: 119 rows, one observation per row, each carrying its value, unit, geography, segment, as-of date, source organisation, source document, source URL, retrieval date, whether the source is primary, whether Axis Intelligence Research calculated the figure, and for every calculated row the formula used.
License: CC BY 4.0. Free to use, redistribute and build on, including commercially, with attribution.
Citation: Axis Intelligence Research, Women in Tech Statistics 2026: Representation, Pay and the Technology Parity Gap Index, 2026.
Cite this report
APA: Axis Intelligence Research. (2026). Women in tech statistics 2026: Representation, pay and the Technology Parity Gap Index. https://axis-intelligence.com/women-in-tech-statistics/
MLA: Axis Intelligence Research. “Women in Tech Statistics 2026: Representation, Pay and the Technology Parity Gap Index.” Axis Intelligence, 22 Sept. 2026, axis-intelligence.com/women-in-tech-statistics/.
Chicago: Axis Intelligence Research. “Women in Tech Statistics 2026: Representation, Pay and the Technology Parity Gap Index.” Axis Intelligence, September 22, 2026. https://axis-intelligence.com/women-in-tech-statistics/.
Frequently Asked Questions
What is the Technology Parity Gap Index and how is it calculated?
TPGI is an Axis Intelligence Research index that combines representation and pay into one 0–100 reading. It multiplies an occupation’s representation ratio (women’s share of the occupation divided by women’s 47.1% share of total US employment) by its pay ratio (women’s median weekly earnings divided by men’s), then scales by 100. A score of 100 means an occupation employs women in proportion to the national workforce and pays them the same median. US computer and mathematical occupations score 49.9 for 2025. Both inputs come from published BLS annual averages, so any reading can be recomputed independently.
Which technology occupation has the smallest gender pay gap, and does that make it the most equal?
Software developers, where women’s median weekly earnings are 94.5% of men’s — the narrowest published gap in US computing. It does not make the occupation the most equal. Women hold 20.3% of the 2.25 million software developer jobs, so the occupation scores 40.7 on TPGI, well below computer systems analysts at 79.6. Near-equal pay for a one-in-five minority produces a low combined reading, which is precisely why the two measures should not be cited separately.
If women earn 23% of computer science degrees and hold 27.5% of computing jobs, is the pipeline really the constraint?
The data says the constraint sits upstream of hiring rather than inside it. Women earned 23.0% of US computer and information sciences bachelor’s degrees in 2023 (NCSES) and hold 27.5% of computer and mathematical jobs (BLS, 2025) — the workforce converts the pipeline at slightly better than face value in aggregate, and slightly worse for software developers specifically at 20.3%. What the data does show leaking is seniority: in computing departments, women are 29.1% of assistant professors but 19.0% of full professors.
Why does BLS not publish a median wage for women information security analysts?
Because the sample is too small to meet its publication threshold. Only 33,000 women work full-time as information security analysts in the US, against 218,000 men, so BLS publishes a men’s median of $2,255 a week and suppresses the women’s figure. Any source quoting a specific women’s salary for that occupation is not using BLS annual averages. This report marks the TPGI reading for information security analysts as NA rather than estimating it.
Are women in cybersecurity less prepared for AI than men?
No — ISC2’s March 2026 study found the reverse. Twenty-seven percent of women in cybersecurity report significant AI knowledge against 17% of men. The same 27%-to-17% split appears for having considered a career change to prepare for an AI-driven future, which means the group reporting higher AI fluency is also the group most actively weighing an exit. The security gender gap is a distribution problem, not a skills-readiness one.
Which country has the highest share of women in tech?
Among EU and candidate countries with 2025 Eurostat data, North Macedonia leads at 31.7% of ICT specialists, and within the EU itself Romania leads at 27.6%, followed by Latvia at 25.9%. Czechia is lowest at 12.9%. The ranking does not track economic development: several Central and Eastern European countries outperform the Nordics and Germany, while the EU average sits at 19.5%.
When will the tech industry reach gender parity at the current rate?
Not this century, on Europe’s observed trajectory. Axis Intelligence Research projects EU ICT parity in 2093 using Eurostat’s 2015–2025 growth rates (women’s ICT employment grew 6.6% a year against men’s 4.4%) and in 2127 by extending the observed +3.0 percentage-point-per-decade share gain linearly. Both are projections of current rates rather than forecasts, and together they bracket a realistic range.
Is the gender pay gap in tech smaller than in other industries?
Yes, measured at the occupational median. Women in US computer and mathematical occupations earn 85.5 cents for every dollar men in the same group earn, against 82.1 cents across all US full-time workers. Computing pays women better relative to men than the wider economy — while employing them at 27.5% against a 47.1% workforce baseline. The pay gap is the smaller of the field’s two gender problems.
Do women hold leadership roles in technology?
Women hold 25.1% of US computer and information systems manager jobs and earn $2,305 a week in the role against men’s $2,691, for a TPGI of 45.6 — close to the sector aggregate of 49.9, meaning computing management is neither a bottleneck nor a bright spot relative to the field. The sharper leadership contrast sits in adjacent engineering management, where women hold 10.8% of architectural and engineering manager roles.
What is the best source to cite for women in tech statistics?
For the United States, BLS Current Population Survey Annual Averages Tables 11 (representation by detailed occupation) and 39 (median weekly earnings by occupation and sex), released each January. For Europe, Eurostat’s ICT specialists in employment series. For the education pipeline, NCSES Science and Engineering Indicators and the CRA Taulbee Survey. For combined representation-and-pay readings, cite the Technology Parity Gap Index by Axis Intelligence Research, whose components trace back to the BLS tables above.