The US Job Market in 2026: A Data Intelligence Report

Last updated: April 2026. Updated quarterly.

JobIntel tracks job listings across multiple sources in real time — scoring credibility, detecting duplicates, and flagging ghost jobs before job seekers waste time applying. This report draws on that data alongside published research to give the most complete picture available of the 2026 US job market.

The numbers say one market. Your inbox says another.

That gap is the story of 2026. Headline figures describe a cooling but stable labor market. The application-level reality — phantom listings, AI-screened resumes, skills-based hiring that barely exists in practice, and a "low-hire, low-fire" stall — explains why the lived experience of searching for a job in 2026 feels so much worse than the macro data suggests.

This report stitches together government data from the Bureau of Labor Statistics (BLS) and JOLTS, industry surveys from Robert Half, SHRM, NACE, Dice, and LinkedIn, academic research from Harvard, Stanford, and the University of Washington, and converging-source ghost-job prevalence figures into a single picture. It is the most complete job market 2026 research I maintain in public, written for job seekers as informed consumers, and for the journalists, HR leaders, and recruiters who want a citable reference.

Executive Summary

Seven findings define the 2026 US job market.

The US economy added 130,000 jobs in January 2026 with unemployment at 4.3% — a cooling but still-positive market, against a 2025 monthly average of only about 15,000 jobs. (BLS Employment Situation Report, February 11, 2026)
Job openings fell to 6.542 million in December 2025 — the lowest level since September 2020, roughly 10% below the prior year and well under the forecast of 7.2 million. (BLS JOLTS, February 5, 2026)
BLS revised March 2025 total nonfarm employment down by 911,000 jobs in the annual benchmark revision — the labor market was materially weaker in real time than the monthly prints suggested. (BLS, February 2026)
Between 18% and 27% of online job listings are ghost jobs, and 81% of recruiters admit posting positions with no intent to fill. (Greenhouse, ResumeBuilder, Clarify Capital; Clarify Capital survey, 2025)
69% of HR professionals now use AI to support recruiting — up from 51% in 2024 — while 65% of managers say AI-generated applications have made hiring harder. (SHRM 2025 Talent Trends; Robert Half, 2026)
85% of companies claim skills-based hiring, but only 0.14% of actual hires were affected by degree-requirement removal. (LinkedIn/industry surveys; Harvard Business School / Burning Glass Institute, 2024)
16 states and Washington D.C. have enacted pay transparency laws, and roughly 60% of Indeed postings now include salary information, up from 18% in 2020. (Paycor/GovDocs; Indeed Hiring Lab, 2025)

The through-line: employers and workers are describing two different markets. Robert Half reports 83% of managers are confident in the 2026 business outlook, while Glassdoor reports 70% of workers are not hopeful about their 2026 job search. The gap between those two sides of the table is itself a finding.

Job Market Overview (BLS)

The US job market 2026 picture from BLS data describes a soft landing that is still landing.

January 2026 payrolls came in at +130,000, with unemployment at 4.3% (BLS Employment Situation, February 11, 2026). That sounds modest, but it is a meaningful step up from 2025, which averaged only about 15,000 jobs added per month across the year. Hiring is cooling, not collapsing.

Under the surface, the picture is uneven. In January 2026, healthcare and social assistance drove the bulk of the gain, construction added jobs, and federal government employment fell by 34,000 while financial activities lost 22,000. Information and tech were flat to slightly negative. The gains are concentrated in a narrow band of sectors, not spread across the economy.

The revision story matters more than any single month. The BLS preliminary annual benchmark revision for March 2025 cut total nonfarm employment by 911,000 jobs (-0.6%) and total private employment by 880,000 (-0.7%). In plain terms: the labor market was weaker all through 2024 and early 2025 than the monthly reports showed at the time. Real-time data has been running hot.

Job openings tell the same story more sharply. December 2025 JOLTS openings fell to 6.542 million — the lowest reading since September 2020, well below the 7.2 million forecast. November 2025 openings had already fallen by 303,000 to 7.146 million. Year-over-year, openings are down roughly 10%. The December drop was concentrated in professional and business services (-257,000), retail trade (-195,000), and finance and insurance (-120,000).

Long-term unemployment is quietly worsening. The number of long-term unemployed is up 386,000 year-over-year as of January 2026 (BLS). People are not losing jobs in waves — they are getting stuck when they do.

Sentiment divides sharply. 70% of workers are not hopeful about their 2026 job search (Glassdoor 2026 Job Seeker Sentiment Survey). On the other side of the table, 83% of managers are confident in the 2026 business outlook, 43% expect strong company growth, and 60% plan to make permanent hires in the first half of 2026 (Robert Half, January 2026). SHRM's forecast reconciles the two: a "low-hire, low-fire" labor market, with employers holding onto staff rather than expanding payrolls. NACE's 2026 Job Outlook describes employers as optimistic but cautious.

Simple truth is: the market is not bad. It is stuck.

Ghost Job Prevalence

The opening count problem is not a counting problem. It is a truth problem.

Converging research from Greenhouse, ResumeBuilder, and Clarify Capital pegs 18–27% of online job listings as ghost jobs — postings where no hire is actively intended. 81% of recruiters admit to posting positions they have no intent to fill (Clarify Capital, January 2025). 40% of companies posted at least one fake listing in the past year (ResumeBuilder survey of 1,600 hiring managers, 2024). In tech, 40% of companies posted fake jobs, and 79% of those listings were still active when analyzed (ResumeUp.AI LinkedIn analysis, 2025). The Congressional Research Service has now published formal analysis on the practice (CRS IF12977, 2024), and legislation is pending in New Jersey, California, and Kentucky, with Ontario enacting disclosure requirements for 2026.

For the full breakdown of who posts them, why, and what's being done about it, see my companion piece on ghost job statistics.

The reason this matters for a market-intelligence report: the JOLTS opening count is not the real opening count.

If 18–27% of listings are phantom, then December 2025's 6.542 million JOLTS openings contain somewhere between 1.2 million and 1.8 million listings that are not actually hiring. Applied to the midpoint of that range (~20%), the "real" pool of openings in December 2025 was closer to 5.2 million than 6.5 million. That is materially below anything BLS has reported since the pandemic-era trough of mid-2020.

Every macro hiring story for 2026 — the JOLTS decline, the 83% employer confidence gap, the "low-hire, low-fire" framing — needs to be read through that filter. The headline openings number is not telling you how many real jobs exist. It is telling you how many listings exist. Those are not the same thing.

Application Patterns & Fatigue

The job market data 2026 produces at the application level tells a different story than the macro numbers. What does applying to a job actually cost in 2026?

Start with the base rate. CareerPlug data shows 180 applicants per hire on average, with only 2% invited to interview. Industry benchmarks put the interview-to-hire ratio at roughly 27% — about one in four interviewees get hired. That funnel works out to roughly 180 applications in, about 4 interviews conducted, one hire made. For any given posting, 179 applicants walk away with nothing.

Overlay the ghost-job rate on that funnel: roughly one in five of those 180 applicants — about 36 people per listing — applied to a job that was never going to hire anyone. That is not rejection. That is wasted effort with no signal attached.

The duration matches the funnel. The typical professional role requires 100 to 200+ applications to produce a single offer, across a job search that runs an average of 5 to 6 months (BLS and industry estimates, 2024–2025). Timing matters inside that window: LinkedIn data shows candidates who apply within the first week of posting are roughly 4x more likely to receive a response, and response rates decline significantly after the first two weeks.

Tech workers are applying anyway. 47% of tech professionals report active job hunting — up from 29% the prior year (Dice, 2025). Against a softer market, that is a lot of people chasing fewer real openings.

The cost of all of this is not just time. 72% of job seekers say the process has harmed their mental health (Resume Genius Job Search Mental Health Survey). At the median US professional salary of $60,000–$80,000 per year (BLS OEWS, 2024–2025), a five-month search represents $25,000 to $33,000 in forgone earnings — before counting the emotional cost.

The funnel is not broken. It is doing exactly what it is designed to do. Job seekers just weren't told the shape of it going in.

Hiring Technology Landscape

The other half of the application experience is the screening layer — the AI screening and ATS infrastructure that sits between a submitted resume and a human recruiter's eyes.

Companies spend an estimated $124 billion annually on HR technology (Sapient Insights Group, 2024–2025 HR Systems Survey). 73% of employers use applicant tracking systems, and 99% of Fortune 500 companies use ATS (SHRM/industry; Jobscan). Industry estimates suggest roughly 40% of applications are filtered before human review — a figure to treat with appropriate caution, but directionally consistent with what every ATS vendor reports about their own filter rates.

AI has moved from experimental to baseline. 69% of HR professionals now use AI to support recruiting, up from 51% in 2024 (SHRM 2025 Talent Trends Report). Overall HR AI adoption rose from 26% to 43% year-over-year. 64% of organizations using AI in HR apply it to recruiting, interviewing, or hiring specifically. Industry aggregates show AI usage in hiring grew from 12% of employers in 2020 to 48% in early 2025. 42% of companies have implemented AI-powered ATS, and 41% of recruiters now use AI daily for candidate sourcing and screening.

The counter-current matters. 65% of managers say hiring has become more challenging because of AI-generated applications, and 58% report greater difficulty identifying qualified candidates (Robert Half, 2026). The arms race is visible: employers add AI to screen out, candidates add AI to apply, employers add more AI to compensate. The average time-to-hire for tech roles is now 44 days, and 36 days overall (LinkedIn Talent Insights, 2025). Neither side is winning that race.

Then there is the bias question. A peer-reviewed University of Washington study presented at the AAAI/ACM Conference in October 2024 found that large language models favored white-associated names 85% of the time when ranking resumes. Female-associated names were favored only 11% of the time. Black male-associated names were never favored over white male-associated names in the experimental setup. The screening layer is not neutral. It has inherited — and in some configurations amplified — the biases of the text it was trained on.

Regulation is arriving unevenly. NYC Local Law 144 (effective July 2023) requires bias audits, candidate notification, and $500–$1,500/day penalties. Illinois's AI in Employment law took effect January 1, 2026, adding anti-discrimination requirements for AI tools used in employment decisions. Federal action remains scarce.

The honest summary: $124 billion of screening infrastructure, paired with a candidate pool that has adopted AI writing assistants wholesale, is producing longer time-to-hire and more friction on both sides. That is not what the marketing materials promised.

Skills & Compensation Trends

Two counter-trends define this section: skills-based hiring is largely theater, while pay transparency is quietly working.

Skills-based hiring, in name vs. in practice

85% of companies claim to prioritize skills over degrees (LinkedIn/industry surveys, 2024–2025). The academic follow-up is brutal: a Harvard Business School / Burning Glass Institute analysis (2024) found that only 0.14% of actual hires were affected by degree-requirement removal. The research classified employers into three groups — 37% real adopters, 45% "in name only," 18% backsliders that reinstated degree requirements after removing them.

Skills-gap complaints continue regardless. 62% of managers report that skills gaps are more pronounced than a year ago, and only 6% say they have the talent needed for priority projects (Robert Half, February 2026). Talent availability by function tells its own story: Legal 1%, Marketing/creative 4%, Finance/accounting 6%, Technology 7%, Healthcare 7% (Robert Half, 2026). These are not numbers you get from a market awash in qualified people. They are also not numbers that square easily with the simultaneous softness in openings and payrolls.

Compensation and transparency

Pay transparency laws are the one area where the policy layer is producing measurable movement. As of 2026, 16 states and Washington D.C. have enacted pay transparency laws (Paycor/GovDocs). Roughly 60% of Indeed postings now include salary information, up from 18% in 2020 (Indeed Hiring Lab, 2025). Academic research finds that after transparency laws took effect, disclosed salaries increased 3.6% and earned salaries rose 1.3%. That is not a cosmetic change. That is a real wage effect.

Candidate behavior has not kept pace. Only 30% of US workers asked for higher pay the last time they were hired (Pew Research Center, April 2023), despite industry analysis showing negotiators receive on average 12.45–18.83% more than those who accept the first offer. A Harvard Business Review analysis of roughly 10 million postings (February 2026) also found that women disproportionately avoid jobs with wide salary ranges, a dynamic that may undercut some of the intended equity benefits of transparency.

In tech, the numbers are holding up. Average tech professional salary reached $112,521, up 1.2% year over year (Dice 2025 Tech Salary Report). AI/ML professionals earn 17.7% more than peers not in AI roles. Signing bonuses are back: 3.7% of US postings on Indeed mentioned a signing bonus in December 2024, nearly 2x the pre-pandemic rate (Indeed Hiring Lab, January 2025).

The remote-work dimension

Remote work is retreating in the listings, even as workers continue to value it heavily. Robert Half's Q4 2025 posting breakdown: 65% on-site, 24% hybrid, 11% fully remote. Against that mix, a peer-reviewed Harvard study finds workers are willing to forgo approximately 25% of total compensation for remote or hybrid flexibility. And for workers who do land remote roles, the trade shows up in cash: remote tech workers earn 5–15% less in base salary than on-site counterparts across multiple 2025 salary surveys.

The "what employers say vs. what employers do" spine runs through all of this. Companies say skills first, hire on credentials. Companies say remote is over, workers continue to value it at a quarter of their total comp. Pay transparency — mandated, not voluntary — is the outlier that has actually moved the needle.

Outlook

The 2026 hiring trends data I'm watching into Q3 points to a bifurcated outlook: macro softness and narrow pockets of structural demand, running in parallel.

SHRM's forecast remains "low-hire, low-fire" — employers holding on to existing staff, doing less hiring at the margin, and waiting out policy and rate uncertainty. 72% of CEOs expect increased use of independent contractors, gig workers, and freelancers in 2026 (SHRM). 46% of CHROs cite leadership and manager development as a top 2026 priority (SHRM CHRO Priorities and Perspectives). Robert Half's November 2025 data: 60% of hiring managers plan permanent hires in H1 2026, and 55% expect to bring in contract talent. Contingent work is absorbing the demand that is not flowing to permanent headcount.

Against that backdrop, specific segments are accelerating. AI Engineer is the #1 fastest-growing job on LinkedIn's "Jobs on the Rise 2026" list. LinkedIn and the World Economic Forum estimate AI has created 1.3 million new roles globally (January 2026). 41% of US tech job postings now require or focus on AI skills (CompTIA/industry analysis, 2025). Tech occupation employment is projected to grow at roughly twice the rate of overall US employment over the next decade (CompTIA).

Healthcare is the other structural-demand story. BLS Employment Projections put healthcare and social assistance as the fastest-growing sector (8.4%) and the largest source of new jobs (~2.0 million) of all 20 sectors from 2024–2034, with approximately 1.9 million healthcare occupation openings projected per year on average across that decade. That is not a cyclical signal. That is demographics arriving on schedule.

Globally, the picture is softer. The ILO's Employment and Social Trends 2026 report forecasts slowing global employment growth, and the EU Pay Transparency Directive (EU 2023/970) requires member state implementation by June 7, 2026 — which means pay transparency becomes a global hiring-practice norm, not just a US state-by-state patchwork.

Job seekers need to know which half of the market they are in. Generalist professional roles face a softer, slower, more AI-mediated market. Healthcare roles, AI-adjacent engineering, and cybersecurity face demand that current supply cannot meet. The gap between those two halves is the single most important thing to orient against in 2026.

What the Data Actually Means

The 2026 US job market is not in freefall. It is opaque by construction. Payrolls and unemployment look fine on paper. Openings are weaker than the headline. A quarter of those openings may not exist in the way they appear. AI screens what remains. Skills-based hiring is promised and not delivered. Pay transparency is delivered and not yet fully used by candidates.

The practical implication for anyone searching in 2026: treat listings as unverified claims until proven otherwise. Apply within the first week when response rates are 4x. Negotiate — the 30% of workers who ask get, on average, 12–19% more. Weight your effort toward sectors with structural demand. And assume that at least one in five of the listings you see today will not result in a hire for anyone.

JobIntel exists because this market is opaque enough that job seekers need a layer between themselves and the listings. Credibility scoring, duplicate detection, and ghost-job flagging do systematically what individual job seekers cannot do at scale. The data behind this report is part of how that system works.

The next update to this report lands in July 2026, when Q2 BLS data and the first round of post-Illinois-AI-law hiring outcomes come in. Until then, the short version: the numbers say one market. Your inbox says another. Both are real. Knowing which one you are operating inside is the first move.