AI Job Market Statistics 2026
By Axis Intelligence Research
Co-author: David Park, Careers and Workforce | Last updated: September 1, 2026 | License: CC BY 4.0
The share of U.S. job postings mentioning artificial intelligence reached 6.28% on July 31, 2026, the highest reading in the Indeed AI Tracker’s seven-year series and nearly double the 3.21% recorded a year earlier. Behind that single number sits a labor market that is not spreading AI demand evenly — it is concentrating it.
Quick Answer
According to Axis Intelligence Research, the United States generated approximately 994,500 AI-skill job postings in 2025, equal to 2.56% of all U.S. postings tracked by Lightcast. Demand has accelerated since: AI mentions hit 6.28% of Indeed postings by July 31, 2026. Median pay for data scientists was $120,230 in May 2025, 2.36 times the all-occupations median of $50,980.
Key Findings
- According to Axis Intelligence Research, the U.S. produced approximately 994,500 AI-skill job postings in 2025, a figure triangulated from three independent state-level derivations that agree to within 243 postings.
- The share of U.S. job postings mentioning AI reached 6.28% on July 31, 2026, up 95.5% from 3.21% on July 31, 2025, per Indeed Hiring Lab’s AI Tracker dataset.
- According to Axis Intelligence Research, the AI Demand Diffusion Index (ADDI) fell from 22.78 in 2024 to 20.18 in 2025, meaning AI hiring demand became more concentrated in the Information sector, not less.
- Texas ranked second nationally in AI posting volume at 8.10% of the U.S. total, yet scored an AI Intensity Quotient of 0.93 — below the national baseline of 1.00, according to Axis Intelligence Research.
- Retrieval augmented generation appeared in 12,609 U.S. AI job postings in 2025, up 337% from 2,885 in 2024, the fastest-growing named generative AI skill in Lightcast’s data.
How Many AI Job Postings Are There in the United States?
Two measurement systems answer this question, and they disagree — for reasons that matter.
The Stanford Institute for Human-Centered Artificial Intelligence, drawing on Lightcast’s posting database, puts AI-skill postings at 2.56% of all U.S. job postings in 2025. That places the U.S. behind Singapore (4.69%), Hong Kong (3.48%), Luxembourg (3.43%), Spain (3.31%) and Canada (3.00%), and ahead of Chile (2.41%) and the United Kingdom (1.93%).
Lightcast publishes the share but not the national count. It does publish three state counts and their shares of the national total, which makes the base recoverable.
Reconstructing the national AI posting base
| Input | Postings | Share of U.S. total | Implied national base |
|---|---|---|---|
| California | 170,881 | 17.18% | 994,651 |
| Texas | 80,547 | 8.10% | 994,407 |
| New York | 66,029 | 6.64% | 994,413 |
| Axis mean | 994,490 |
Source: Lightcast via Stanford HAI 2026 AI Index, Figures 4.4.10–4.4.12; calculation by Axis Intelligence Research.
Three independent derivations land within 243 postings of each other — a spread of 0.024%. According to Axis Intelligence Research, that convergence is strong evidence the underlying figure is roughly 994,500 U.S. AI job postings in 2025. Divide by the 2.56% national share and the implied total U.S. posting volume for the year is about 38.85 million.
The second system is Indeed Hiring Lab’s AI Tracker, a daily series published under CC BY 4.0. Axis Intelligence Research retrieved the underlying dataset on September 1, 2026. Its readings run higher than Lightcast’s because it counts postings that mention AI keywords rather than postings that require an AI skill.
| Date | AI share of U.S. postings |
|---|---|
| January 1, 2019 | 1.72% |
| March 13, 2022 | 3.29% (pre-generative-AI peak) |
| November 30, 2022 | 2.21% |
| June 29, 2023 | 1.69% (series trough) |
| December 31, 2024 | 2.71% |
| December 31, 2025 | 4.43% |
| July 31, 2026 | 6.28% |
Source: Indeed Hiring Lab, AI Tracker (AI_posting.csv), retrieved September 1, 2026.
That trough is the part most coverage skips. AI mentions were falling through mid-2023, seven months after ChatGPT shipped. The climb from 1.69% to 6.28% took three years, and 184% of the total gain came after November 2022.
David Park: The gap between 2.56% and 6.28% isn’t an error in either dataset — it’s the difference between “we need someone who can build this” and “we’d like someone who’s used it.” Both are real requisitions. If you’re deciding what to put on a résumé, the narrower Lightcast number is the one that describes competitive, well-paid roles. The broader Indeed number tells you something else, and something arguably more useful: AI language is becoming standard furniture in job ads across the whole posting universe.
Source: Axis Intelligence Research — CC BY 4.0
Which Industries Are Hiring for AI Skills?
The Information sector — publishing, broadcasting, telecom and software — carries AI demand at a density no other sector approaches.
| NAICS sector | 2024 | 2025 | Change | Source |
|---|---|---|---|---|
| Information | 7.82% | 13.22% | +69.1% | Lightcast / Stanford HAI |
| Professional, scientific and technical services | 4.41% | 6.49% | +47.1% | Lightcast / Stanford HAI |
| Finance and insurance | 3.27% | 5.33% | +62.9% | Lightcast / Stanford HAI |
| Manufacturing | 3.35% | 4.66% | +39.3% | Lightcast / Stanford HAI |
| Management of companies and enterprises | 1.62% | 3.28% | +102.3% | Lightcast / Stanford HAI |
| Utilities | 2.00% | 2.89% | +44.4% | Lightcast / Stanford HAI |
| Educational services | 2.03% | 2.42% | +19.1% | Lightcast / Stanford HAI |
| Real estate and rental and leasing | 1.08% | 2.08% | +93.5% | Lightcast / Stanford HAI |
| Wholesale trade | 1.06% | 1.93% | +83.0% | Lightcast / Stanford HAI |
| Mining, quarrying, oil and gas | 1.74% | 1.87% | +7.6% | Lightcast / Stanford HAI |
| Public administration | 1.19% | 1.69% | +41.6% | Lightcast / Stanford HAI |
| Retail trade | 1.04% | 1.67% | +60.3% | Lightcast / Stanford HAI |
| Agriculture, forestry, fishing and hunting | 0.99% | 1.32% | +33.0% | Lightcast / Stanford HAI |
| Transportation and warehousing | 0.81% | 1.26% | +55.4% | Lightcast / Stanford HAI |
| Waste management and admin support | 0.35% | 0.46% | +30.8% | Lightcast / Stanford HAI |
Share of each sector’s own job postings requiring at least one AI skill. Source: Lightcast, published in Stanford HAI 2026 AI Index Figure 4.4.9.
The AI Demand Diffusion Index (ADDI)
ADDI — AI Demand Diffusion Index. An Axis Intelligence Research metric measuring how far AI hiring demand has spread beyond the technology sector, on a 0–100 scale. Higher readings mean broader diffusion.
Formula: ADDI = 100 × (unweighted mean AI posting share of the 14 non-Information NAICS sectors ÷ Information sector AI posting share)
Worked example, 2025: the 14 non-Information shares sum to 37.35, giving a mean of 2.6679. Information stands at 13.22. ADDI = 100 × (2.6679 ÷ 13.22) = 20.18.
Worked example, 2024: mean 1.7814, Information 7.82. ADDI = 100 × (1.7814 ÷ 7.82) = 22.78.
| Reading | ADDI | Non-Information mean | Information | Absolute gap |
|---|---|---|---|---|
| 2024 | 22.78 | 1.78% | 7.82% | 6.04 pp |
| 2025 | 20.18 | 2.67% | 13.22% | 10.55 pp |
Original metric. Inputs: Lightcast sector shares via Stanford HAI 2026 AI Index. Calculation by Axis Intelligence Research.
According to Axis Intelligence Research, ADDI fell 2.60 points in a single year. The rest of the economy grew its AI posting share by 49.8% — genuinely fast — while Information grew 69.1%. The gap between the tech sector and everyone else widened from 6.04 to 10.55 percentage points, a 74.7% expansion.
This cuts against the prevailing read of the same data. Lightcast’s own commentary on the 2026 AI Index frames the sector numbers as evidence that AI has stopped being “a tech thing.” Both statements describe the same table. Every sector did grow, and the low-adoption sectors grew meaningfully. But relative to the Information sector, the rest of the economy lost ground in 2025. Diffusion in absolute terms and concentration in relative terms are happening simultaneously, and which one you report determines the headline.
Scope of ADDI: the index treats each NAICS sector equally and does not weight by sector employment. It measures posting density, not posting volume — a large sector with a low share can still generate more AI requisitions than Information. Readings are comparable across years only while Lightcast’s AI skills taxonomy and sector definitions hold constant.
David Park: If you work in insurance or manufacturing and you have been told the AI hiring wave is coming to your industry, the data says it already has — finance and insurance now runs 5.33%, up from 3.27%. What the data also says is that the tech sector is pulling away faster than you are catching up. For a career decision, that means the fastest route into AI work still runs through an employer whose product is software. It does not mean your industry has no AI requisitions.
Which States Have the Strongest AI Hiring Demand?
Volume and intensity are different questions, and the answers diverge sharply.
California posted 170,881 AI job listings in 2025, 17.18% of the national total. Texas followed at 80,547 (8.10%) and New York at 66,029 (6.64%). Those three states hold roughly a third of all U.S. AI postings between them. California’s share has been falling for over a decade — from above 25% in 2012 to 17.18% in 2025 — even as the state kept its lead.
The AI Intensity Quotient (AIQ)
AIQ — AI Intensity Quotient. An Axis Intelligence Research metric expressing how AI-dense a state’s labor market is relative to the country as a whole.
Formula: AIQ = (AI share of that state’s own job postings) ÷ (national AI share of 2.56%)
A reading of 1.00 means a state hires for AI at exactly the national rate. Above 1.00 means AI work is over-represented in that state’s requisitions.
| State | AI share of own postings | AIQ | Reading |
|---|---|---|---|
| District of Columbia | 6.20% | 2.42 | Most AI-dense labor market in the country |
| Delaware | 4.40% | 1.72 | Financial and corporate-domicile effect |
| California | 4.26% | 1.66 | Leads on both volume and intensity |
| Washington | 4.03% | 1.57 | 3.93% of national volume, far denser than its size |
| New York | 3.21% | 1.25 | Above baseline |
| Texas | 2.38% | 0.93 | Second in volume, below the national baseline |
Original metric. Inputs: Lightcast state-level shares via Stanford HAI 2026 AI Index Figures 4.4.13–4.4.14. Calculation by Axis Intelligence Research.
Texas is the finding worth sitting with. According to Axis Intelligence Research, Texas ranks second in the country by AI posting volume and 0.93 by intensity — a labor market large enough to generate 80,547 AI listings while still advertising AI roles at a slightly lower rate than the national average. Washington is the mirror image: 39,083 AI postings, less than half of Texas’s count, at an intensity 69.3% higher.
Washington, D.C. clearing 2.42 reflects federal procurement, contractor hiring and policy roles rather than a commercial AI cluster.
Scope of AIQ: the quotient measures advertised demand, not filled employment, and state posting mixes are shaped by industry composition. A state dominated by logistics or hospitality employment will score low regardless of how much AI work its tech firms do.
What AI Skills Do U.S. Employers Actually Ask For?
Two answers, depending on whether you want the volume or the velocity.
By volume: the skills on the most requisitions
| Skill | 2025 AI postings | 2013–15 baseline | Growth |
|---|---|---|---|
| Python | 258,674 | 52,678 | +391% |
| Computer science | 257,127 | 97,085 | +165% |
| Scalability | 197,744 | 23,727 | +733% |
| Automation | 190,758 | 26,870 | +610% |
| Workflow management | 186,325 | 20,295 | +818% |
| Data analysis | 170,396 | 54,942 | +210% |
| SQL | 151,191 | 65,300 | +132% |
| Project management | 149,865 | 60,745 | +147% |
| Data science | 142,120 | 26,767 | +431% |
| Amazon Web Services | 142,037 | 9,742 | +1,358% |
Source: Lightcast, published in Stanford HAI 2026 AI Index Figure 4.4.4. A single posting can list multiple skills.
Python appears in 258,674 AI postings. Against the reconstructed national base, that is 26.0% of all U.S. AI job postings in 2025, according to Axis Intelligence Research. Four of the top ten are not machine learning skills at all — scalability, automation, workflow management and project management describe the work of putting a model into production and keeping it there.
Amazon Web Services grew 1,358% from the 2013–15 baseline, the steepest rise in the table.
By velocity: the skills growing fastest year over year
| Generative AI skill | 2024 postings | 2025 postings | Growth |
|---|---|---|---|
| Retrieval augmented generation | 2,885 | 12,609 | +337% |
| Prompt engineering | 6,152 | 22,227 | +261% |
| Generative artificial intelligence | 65,557 | 138,188 | +111% |
| Large language modeling | 19,045 | 38,526 | +102% |
Source: Lightcast, published in Stanford HAI 2026 AI Index Figure 4.4.5.
At the cluster level, the term “artificial intelligence” appeared in 1.70% of all U.S. job postings in 2025, machine learning in 0.99%, generative AI in 0.41% and AI agents in 0.23%. AI ethics, governance and regulations sat at 0.05% — the smallest cluster measured, and the one most likely to move if federal or state AI rules tighten.
David Park: Prompt engineering was supposed to be the job title that died in 2025. It grew 261% as a skill line inside other people’s requisitions instead. That’s the pattern to watch across this whole table: AI capabilities are being absorbed into existing comp bands rather than spun out into new ones. Retrieval augmented generation at +337% is the single clearest signal of what employers are building right now — systems that connect a model to a company’s own documents. If you want one thing to learn that shows up on a hiring manager’s checklist in 2026, it is that.
What Do AI Jobs Pay in 2026?
The U.S. Bureau of Labor Statistics publishes the only U.S. pay figures collected from employers rather than from job ads. These are May 2025 medians.
| Occupation | Median annual wage | Ratio to all-occupations median | Source |
|---|---|---|---|
| Computer and information research scientists | $140,300 | 2.75× | BLS OEWS |
| Software developers, QA analysts and testers | $134,040 | 2.63× | BLS OEWS |
| Computer network architects | $134,050 | 2.63× | BLS OEWS |
| Information security analysts | $129,180 | 2.53× | BLS OEWS |
| Database administrators and architects | $126,760 | 2.49× | BLS OEWS |
| Data scientists | $120,230 | 2.36× | BLS OEWS |
| Computer and IT occupations (group) | $109,470 | 2.15× | BLS OEWS |
| Computer systems analysts | $105,850 | 2.08× | BLS OEWS |
| Computer programmers | $100,390 | 1.97× | BLS OEWS |
| Web developers and digital designers | $99,520 | 1.95× | BLS OEWS |
| Network and systems administrators | $99,130 | 1.94× | BLS OEWS |
| All occupations | $50,980 | 1.00× | BLS OEWS |
Source: BLS Occupational Employment and Wage Statistics, May 2025. Ratios calculated by Axis Intelligence Research.
The data scientist band runs wide. The bottom 10% earned under $67,240; the top 10% cleared $199,130. Industry placement moves the median by $33,590: publishing, broadcasting and content providers paid $142,240, while insurance carriers paid $108,650.
The advertised premium, and why we won’t convert it to dollars
PwC’s 2026 Global AI Jobs Barometer, built on more than one billion job ads including 449.1 million from the United States, puts the average wage premium for postings requiring at least one AI skill at 61.9% in 2025, up from 57%. By sector: consumer markets 118%, technology/media/telecoms 84%, energy and utilities 75%, manufacturing 73%, professional services 67%, financial services 53%, health industries 37%, government and public sector 16%.
Axis Intelligence Research does not multiply that 61.9% by BLS median wages, and states the reason plainly. PwC’s premium compares advertised salaries within a sector between AI and non-AI postings, and PwC explicitly notes the estimate does not control for education, experience or location. BLS medians measure actual wages paid to incumbent workers across all employers. Multiplying an uncontrolled advertised-salary spread by an employer-survey median produces a dollar figure with no defensible meaning. Two figures side by side, honestly labeled, are more useful than one composite that cannot be defended.
Where the openings actually come from
BLS projects data scientist employment rising from 275,600 in 2025 to 371,000 in 2035 — 35% growth, against 3% for all occupations. That headline understates the hiring volume. BLS also projects 24,800 openings per year, or 248,000 across the decade, while net employment rises by only 95,400. According to Axis Intelligence Research, 61.5% of data scientist openings over the next decade will come from replacement rather than growth — people retiring or moving to other occupations. Across all computer and IT occupations, BLS projects about 280,000 openings a year.
What Is Happening to Entry-Level AI Jobs?
This is where the demand-side data turns uncomfortable, and where the U.S.-specific numbers matter most.
PwC’s analysis of U.S. entry-level postings splits early-career roles in the most AI-exposed quartile into two groups. Roles that added traditionally senior skills — stakeholder management, strategic decision making, mentorship, people management — grew 35% between 2019 and 2025. Roles that did not add those skills fell 10%. Same quartile, same period, a 45-point spread.
The skill load rose with exposure. Entry-level postings in the top AI-exposure quartile added an average of 207 new skills per occupation since 2019, against 144 in the bottom quartile. In the top quartile, 52% of those new skills were ones that appeared almost exclusively in experienced-hire postings in 2019. In the bottom quartile, 7% were.
Stanford’s data shows the employment consequence. Employment for software developers aged 22 to 25 had fallen close to 20% from its 2022 peak by September 2025, while headcount for older cohorts kept growing. Among workers aged 22 to 25 generally, employment in the most AI-exposed occupations ran roughly 16% below the least-exposed, after controlling for firm-level effects.
The unemployment data complicates the story rather than confirming it. From 2022 to early 2025, unemployment rose 0.30 percentage points for workers in the most AI-exposed quintile and 0.94 points for the least exposed. Exposure to AI is not what drove the aggregate unemployment increase. The damage shows up in hiring pipelines, not in separations.
David Park: The 11pm version of this fear is “there is no entry-level anymore.” The data does not support that, and the difference is worth being precise about. Entry-level AI-exposed postings that ask for judgment grew 35%. The ones that ask only for task execution shrank 10%. The bottom rung didn’t disappear; it moved up, and it now expects things that used to be a second-promotion skill set. If you are two years out of school, the practical read is that the interview you’re preparing for is closer to a senior interview than the job title suggests.
For a fuller treatment of the displacement side of this ledger, see our analysis of AI job displacement statistics and AI job loss statistics, which cover measured reductions rather than demand. Sector-level hiring contraction is tracked in our tech layoffs statistics.
Who Is Hiring, and What Does the Talent Pool Look Like?
PwC’s firm-level data points somewhere unexpected: the most AI-exposed companies grew headcount 52.2% against a 2018 baseline, versus 35.7% at the least exposed. That comes from an ORBIS sample restricted to firms with at least $50 million in turnover that survived the whole period, so survivorship bias is real and PwC says so. Within that limit, the firms deepest into AI are the ones adding people.
Globally, AI specialist postings grew 68.9% from 2024 to 2025 while total postings grew 8.6%. PwC classifies 22% of advertised jobs as “professionalised” by AI — roles where AI absorbs routine work and leaves the expert judgment to people — and 52% as “democratised,” where AI takes on the complex part. Advertised salaries for professionalised roles grew 37% since 2021 against 26% for democratised roles.
Two composition facts round out the picture. Women make up 34.26% of U.S. AI talent on LinkedIn, a ratio that has barely shifted since 2016 despite the pool expanding. And the U.S. remains a net importer of AI talent at 1.22 per 10,000 LinkedIn members — positive, but well behind Luxembourg (5.23) and the UAE (4.40).
Employer expectations run cooler than posting data. In McKinsey’s survey published in the 2026 AI Index, 33% of organizations expected AI to reduce headcount over the coming year, while 43% expected little or no change.
Adjacent demand data for the security side of this market is in our cybersecurity jobs statistics, and the broader market context sits in our AI statistics reference page.
Methodology
Collection. Axis Intelligence Research fetched every source in this analysis on September 1, 2026. Four external primary sources supply all reported figures: the U.S. Bureau of Labor Statistics Occupational Outlook Handbook and Occupational Employment and Wage Statistics (May 2025 wages, 2025–35 projections); Stanford HAI’s 2026 AI Index Report Chapter 4, which publishes Lightcast, LinkedIn and McKinsey labor-market series; PwC’s 2026 Global AI Jobs Barometer; and Indeed Hiring Lab’s AI Tracker, whose daily dataset Axis retrieved directly from its public repository under CC BY 4.0. No aggregator or secondary summary was used.
ADDI construction. ADDI = 100 × (mean AI posting share of the 14 non-Information NAICS sectors ÷ Information sector share). Each sector is weighted equally. Both the 2024 and 2025 readings are computed by Axis from the same published table, so the two-point series is internally consistent. The 2025 reading of 20.18 is the current reading; 22.78 is the 2024 reference.
AIQ construction. AIQ = state AI share of its own postings ÷ national AI share (2.56%). Both numerator and denominator come from the same Lightcast 2025 series, so the ratio is basis-consistent.
National base reconstruction. Three state posting counts were each divided by that state’s published share of the national total. The three results were averaged. The 243-posting spread across independent derivations is the check on the method.
What this reading does not capture. Job postings measure advertised demand, not hires, not filled roles, and not employment. Lightcast and Indeed use different keyword taxonomies, which is why their national shares differ by design rather than by error. PwC’s wage premium is an advertised-salary spread that does not control for education, experience or location. McKinsey and LinkedIn figures are self-reported or platform-derived and describe their samples, not the U.S. workforce. All 2025-dated posting figures are annual aggregates; the 6.28% Indeed reading is a seven-day trailing average on a single date.
Deliberate omission. Axis Intelligence Research declined to publish a dollar-value AI wage premium. The available inputs — an uncontrolled advertised-salary spread and an employer-survey wage median — cannot be combined without producing false precision. The refusal is published as a finding.
About This Dataset
ai-job-market-statistics-2026.csv contains 253 rows covering U.S. AI job posting shares, sector and state breakdowns, skill-level posting counts, BLS wage and projection data, PwC premium and entry-level figures, and every Axis-calculated value including the full ADDI and AIQ inputs. Each row carries its value, unit, as-of date, geography, segment, source organization, source document, source URL, retrieval date, primary-source flag, Axis-calculated flag, method note and data type.
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
- Coverage: United States (with global comparison rows clearly labeled), 2013–2026
- Rows: 253 — 202 reported, 43 Axis-calculated, 8 original-metric
How to Cite This Research
APA: Axis Intelligence Research & Park, D. (2026). AI job market statistics 2026: U.S. postings, salaries, skills and where demand is really growing. Axis Intelligence. https://axis-intelligence.com/ai-job-market-statistics/
MLA: Axis Intelligence Research, and David Park. “AI Job Market Statistics 2026: U.S. Postings, Salaries, Skills and Where Demand Is Really Growing.” Axis Intelligence, 1 Sept. 2026, axis-intelligence.com/ai-job-market-statistics/.
Chicago: Axis Intelligence Research and David Park. “AI Job Market Statistics 2026: U.S. Postings, Salaries, Skills and Where Demand Is Really Growing.” Axis Intelligence, September 1, 2026. https://axis-intelligence.com/ai-job-market-statistics/.
Frequently Asked Questions
Why do Lightcast and Indeed report different AI job posting shares for the same country?
They measure different things. Lightcast counts postings that require at least one skill from its AI skills taxonomy, producing 2.56% for the U.S. in 2025. Indeed Hiring Lab counts postings that mention any keyword from a broader AI basket, producing 4.43% at the end of 2025 and 6.28% by July 31, 2026. Neither is wrong. A posting asking for “familiarity with ChatGPT” clears Indeed’s bar and not Lightcast’s.
Is an “AI job posting” the same thing as an AI job?
No, and the distinction matters for anyone reading these numbers as a hiring forecast. A posting is an advertised requisition. It may be filled, cancelled, reposted across multiple boards, or never funded. Posting data measures employer intent at the moment of advertising. BLS employment and wage data measures people actually working and being paid, which is why this analysis uses both.
Does a 62% AI wage premium mean someone with AI skills earns 62% more?
Not as an individual forecast. PwC’s 61.9% figure compares average advertised salaries on AI-requiring postings against non-AI postings in the same sector, and PwC states it does not control for education, experience or location. Those AI postings skew toward senior, technical and metropolitan roles that would pay more regardless. The premium is real as a market signal; it is not a raise anyone can expect from adding a skill line.
Which state hires most intensively for AI, and why isn’t it Texas?
By AI Intensity Quotient, Washington, D.C. leads at 2.42, then Delaware (1.72), California (1.66) and Washington state (1.57). Texas ranks second nationally in raw AI posting volume — 80,547 listings, 8.10% of the U.S. total — but scores 0.93 on intensity. Its labor market is large enough to generate substantial AI hiring while its overall posting mix, weighted toward energy, logistics and healthcare, keeps the density just below the national rate.
Do I need Python to get an AI job in 2026?
Python appears in 258,674 U.S. AI job postings, roughly 26% of the national total, making it the most-requested specialized skill. It is not universal. Four of the top ten skills — scalability, automation, workflow management, project management — are deployment and coordination skills rather than programming. The share of AI postings that never mention Python is larger than the share that does.
Which AI skill is growing fastest in U.S. job postings right now?
Retrieval augmented generation, up 337% from 2,885 postings in 2024 to 12,609 in 2025. Prompt engineering follows at +261%. Both grew faster than the generative AI category as a whole (+111%), which indicates employers are moving from general AI familiarity toward specific system-building skills.
Are entry-level AI roles disappearing?
They are bifurcating. In the most AI-exposed quartile of U.S. entry-level postings, roles that added traditionally senior skills grew 35% between 2019 and 2025 while roles that did not shrank 10%. Employment for software developers aged 22 to 25 fell close to 20% from its 2022 peak by September 2025. The entry-level tier still exists, but its skill requirements now overlap heavily with what used to be mid-career expectations.
If AI hiring is spreading to every sector, why does the tech sector still dominate?
Because absolute spread and relative concentration are both happening. Every one of the 15 NAICS sectors increased its AI posting share in 2025, and the 14 non-Information sectors grew a combined 49.8%. Information grew 69.1%. According to Axis Intelligence Research, that pushed the AI Demand Diffusion Index down from 22.78 to 20.18 and widened the tech-to-everyone-else gap from 6.04 to 10.55 percentage points.
How many AI job postings did the United States generate in 2025?
Approximately 994,500, according to Axis Intelligence Research. Lightcast publishes the national share (2.56%) and three state counts with their national shares; dividing each state count by its share yields 994,651, 994,407 and 994,413, which average to 994,490. That implies roughly 38.85 million total U.S. job postings for the year.
Will AI job demand keep growing at this rate?
The Indeed AI Tracker has risen every quarter since mid-2023, reaching 6.28% on July 31, 2026. It also fell through the first half of 2023, from a March 2022 peak of 3.29% down to 1.69%, so this series has reversed before. BLS projects 35% growth in data scientist employment through 2035 and about 280,000 annual openings across all computer and IT occupations, which sets a floor independent of posting-share volatility.