🔍 Read the full analysis: How To Read The US Data On AI, Growth, And Hours Worked on ThorstenMeyerAI.com
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TL;DR
US output and productivity have risen while hours worked and hiring have grown much more slowly. The figures describe a striking gap, but they do not establish that AI caused it; the effects are uneven across industries and workers.
US output is growing much faster than the hours people work, but the latest labor and productivity figures do not establish that artificial intelligence is responsible. An analysis published November 1 by Thorsten Meyer draws on data from the Bureau of Economic Analysis (BEA), Bureau of Labor Statistics (BLS) and Census Bureau: business-sector output rose 10.0% from the end of 2022 to the second quarter of 2026, while hours worked rose 0.9%, a gap that matters for hiring, pay and how the gains from growth are distributed.
The latest top-line growth figure is strong. The BEA’s advance estimate, released October 29, put real gross domestic product growth at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter. Consumer spending, investment and government spending contributed to the increase. GDP measures the economy as a whole; the BLS productivity figures discussed in Meyer’s analysis cover the narrower nonfarm business sector, excluding farms, government, nonprofits and households.
In that business sector, BLS data show output grew 2.5% in the year to the second quarter of 2026, while hours worked rose 0.2%. Productivity—the amount of output produced per hour—grew 2.2% over that period. Meyer’s calculation from BLS indexes finds that from the fourth quarter of 2022 to the second quarter of 2026, output rose 10.0% and hours worked rose 0.9%. These measures cover different periods and should not be treated as the same comparison.
The labor market picture is mixed. Payroll employment increased by 496,000 in the 12 months to September, according to the source analysis, with health care and social assistance adding 520,000 jobs. Information industries lost 120,000 jobs over that period and remained 12% below their November 2022 peak. The figures indicate that job gains were concentrated in some sectors while others contracted; they do not, by themselves, identify why those changes occurred.
Infographic 01 · More output, same hours
Ten percent more output, almost the same hours
The US business sector produces much more than three years ago with almost no extra work. The new jobs are mostly in health care.
The last 12 months
Nonfarm business sector, Q2 2025 to Q2 2026
- Outputreal, value added+2.5%
- Productivityoutput per hour+2.2%
- Hours workedall workers+0.2%
Where the jobs went
Payroll jobs, change over 12 months to Sep 2026 (preliminary)
Since Q4 2022: output +10.0%, hours +0.9%, productivity +9.1% (my arithmetic from the BLS indexes). Hiring rate in Aug 2026: 3.3% of jobs (2019 average 3.9%); layoff rate 1.0% (2019: 1.2%). Correlation, not proof of cause.
Sources: BLS, Productivity and Costs Q2 2026 (3 Sep 2026) · BLS, Employment Situation Sep 2026 · BLS, JOLTS Aug 2026.
Powered by Thorsten Meyer AI
Productivity Gains Meet Uneven Hiring
When output grows faster than hours worked, businesses can produce more without adding labor at the same rate. That can raise productivity and support economic growth, but it does not automatically mean workers share in the gains through higher pay, more jobs or shorter working hours. The distribution of those gains matters to employees, job seekers and businesses deciding how to staff and invest.
Meyer’s analysis reports that the labor share—the portion of business-sector output paid to workers as wages and benefits—fell to 52.8% in the second quarter of 2026, the lowest level in the series beginning in 1947. It also reports that real private-sector wages fell 0.6% in the year to September. Those figures offer a reason to look beyond GDP growth, though they do not alone explain the causes of changes in workers’ compensation.
Job conditions also vary by age and race. The analysis puts overall unemployment at 4.2%, compared with 8.0% for people aged 20 to 24 and 7.0% for Black workers. It says those subgroup rates were up from 5.5% and 4.8%, respectively, in April 2023. A single national unemployment rate can therefore obscure pressure on particular groups, especially when hiring is slow even as layoffs remain low.
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What the Productivity Numbers Measure
Productivity is calculated as output divided by hours worked. It can rise because businesses make more with the same hours, or because they produce a similar amount with fewer hours. It is an economy-wide measure, not a direct count of AI-generated work or a test of whether a specific technology caused an increase.
The longer-term comparison in Meyer’s analysis shows BLS nonfarm business productivity growing at an average annual rate of 2.1% from the end of 2019, compared with 1.5% a year from 2007 to 2019. The author also calculates an average pace of roughly 2.5% a year from the end of 2022 to the second quarter of 2026. Those estimates describe different periods, and the shorter window does not establish that the change began with, or resulted from, generative AI.
The source places the figures against public debate about AI’s labor-market effects. It references an October 31 Financial Times opinion column by John Burn-Murdoch, whose summary says productivity is up and technology-sector employment down, while the picture elsewhere is less clear. It also notes a Wall Street Journal headline about strong growth not reaching everyone. Meyer says the full articles were behind paywalls and that his assessment relies on public statistics rather than claims about their full arguments.
“Numbers can show that two things happen at the same time. They rarely show that one causes the other.”
— Thorsten Meyer
AI’s Role Is Not Yet Established
The data show productivity growth and changes in employment, but they do not isolate the effect of AI from other factors. The source analysis reports that about one in four US businesses said it used AI in early October, citing the Census Bureau. That measure does not specify how extensively businesses used the technology or how much it contributed to their output.
Technology-sector employment also began declining before generative AI was widely used in businesses, according to Meyer. That timing complicates a simple cause-and-effect account. Investment in computers and software contributed to recent growth, but investment spending is not the same as measured productivity gains from AI in day-to-day work.
The available figures also leave open how workers experience the shift: whether firms are replacing tasks, slowing recruitment, reorganizing work or responding to other economic conditions. The reported wage and labor-share measures raise questions about how growth is divided, but they do not identify a single cause. Longer-term data and more direct measures of workplace adoption will be needed to clarify the connection.
Watch Hiring, Pay and Adoption
The next useful evidence will come from subsequent BLS releases on productivity, hours, employment and wages, alongside BEA updates to GDP estimates. Revisions can change the measured pace of growth, so the current figures should be read as the latest available estimates rather than a final account of 2026.
Future Census Bureau measures of business AI use may help show whether adoption is spreading, but adoption rates alone will not prove an effect on jobs or output. Readers should compare those measures with industry-level hiring, hours and productivity data over time. For now, the confirmed development is a pronounced gap between output growth and hours worked; whether AI is a major cause, and how workers will share the resulting gains, remains unresolved.
Key Questions
What is the main finding in the analysis?
Business-sector output rose 10.0% from the end of 2022 to the second quarter of 2026, while hours worked rose 0.9%, according to Meyer’s calculations from BLS indexes. The figures show a gap between output and hours, not its cause.
Does the data prove AI is reducing jobs?
No. The figures show productivity growth and job losses in some industries, but they do not establish that AI caused either. The analysis says AI use was reported by about one in four US businesses in early October, without measuring how much it changed output or staffing.
How fast did the US economy grow in the third quarter?
The BEA’s October 29 advance estimate put real GDP growth at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter. This is an estimate of overall economic growth, distinct from the BLS’s nonfarm business productivity measures.
Were jobs increasing or decreasing?
Payrolls rose by 496,000 in the 12 months to September, according to the source analysis. Health care and social assistance added 520,000 jobs, while information industries lost 120,000. The national total conceals substantial differences among sectors.
What should readers watch next?
Watch updated BLS data on productivity, hours, wages and employment, along with BEA GDP revisions and further Census Bureau measures of business AI use. Together, these can help track the pattern, but more evidence is needed to establish whether AI is causing it.
Source: ThorstenMeyerAI.com
