🔍 Read the full analysis: US Growth With Almost The Same Hours: Reading The AI Evidence on ThorstenMeyerAI.com
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TL;DR
US business-sector output increased 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked rose 0.9%, according to calculations from BLS indexes cited by Thorsten Meyer. The pattern points to faster productivity growth, but the available figures do not establish that AI caused it or explain how the gains are distributed.
US business output has risen much faster than hours worked since late 2022, according to government statistics cited in a November 1 analysis by Thorsten Meyer, a pattern that has prompted questions about whether AI is changing employment. BLS index figures calculated by Meyer show output up 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked increased 0.9%. The figures indicate stronger productivity, but do not establish that AI caused the gap.
The latest available labor productivity figures cited by Meyer show that, over the year to the second quarter of 2026, nonfarm business output grew 2.5% while hours worked increased 0.2%. Productivity rose 2.2% over that period. The measure covers private businesses other than farms; it does not include government, nonprofits or households.
Productivity growth has also run faster than in the preceding period. Meyer’s analysis reports average annual growth of 2.1% since the end of 2019, compared with 1.5% from 2007 to 2019. Separately, the Bureau of Economic Analysis’ 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. GDP and the BLS business-sector productivity measure cover different parts of economic activity.
Employment growth has been concentrated in some industries. Payrolls increased by 496,000 in the 12 months to September, according to the figures in Meyer’s account; health care and social assistance added 520,000 jobs, while information industries lost 120,000 and remained 12% below their November 2022 employment peak. The article also cites a Census Bureau finding that about one in four US businesses reported using AI in early October. These figures describe concurrent trends, not proof that AI drove the employment changes.
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 and Uneven Hiring
The gap between output and hours matters because it can reflect businesses producing more with each hour of labor. If sustained, faster productivity growth could support higher economic output without a corresponding increase in working time. But the headline growth rate alone does not show whether workers share in those gains, whether fewer people are being hired, or how the changes vary across industries and age groups.
Meyer’s account points to signs that the benefits and pressures are uneven. It reports that the labor share—the portion of business output paid as wages and benefits—fell to 52.8% in the second quarter, the lowest level in the series dating to 1947. It also reports that real private-sector wages fell 0.6% over the year to September. These figures do not, on their own, show that AI caused lower labor income or wages.
Conditions for younger workers and some groups have also worsened in the figures presented. Overall unemployment was 4.2%, compared with 8.0% for people aged 20 to 24 and 7.0% for Black workers. A slowdown in hiring can make it harder for new entrants to find work even when layoffs remain low. For workers, employers and policymakers, the central issue is whether productivity gains will translate into broader pay and job opportunities.
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The AI Timing Question
Debate about AI’s role intensified after generative AI tools became widely visible following ChatGPT’s launch on November 30, 2022. Meyer uses the end of 2022 as a reference point for comparing output and hours. That timing makes the comparison relevant to the AI discussion, but a before-and-after pattern is not a test of cause and effect.
The analysis was published after two prominent media developments: a Financial Times opinion column on October 31 asked whether the data were the first clear evidence of AI’s labor-market impact, and The Wall Street Journal published a headline about economic growth not reaching everyone. Meyer says he could access the FT headline and summary and the WSJ headline, but not the full articles. His numerical case instead relies on primary data from the BLS, BEA, Census Bureau, Federal Reserve and Eurostat.
Other explanations may fit the same broad pattern. Businesses can raise output per hour through investment, process changes, shifts in demand or changes in the kinds of industries growing fastest, as well as through AI. Meyer also notes that US information-sector employment had begun declining before generative AI was in wide business use. Establishing AI’s contribution requires more than observing that productivity rose after late 2022.
What the Data Cannot Establish
The central unknown is how much, if any, of the productivity increase is attributable to AI. The output-hours comparison covers a period that overlaps with rapid AI development, but it does not isolate AI from other influences. The reported Census finding that about one in four businesses used AI in early October also does not measure how intensively they used it or how much it changed output, staffing or hours.
It is also unclear whether the current productivity pace will persist, how its gains are divided among workers and businesses, and whether weak hiring will spread beyond particular industries or groups. The figures in the analysis combine measures with different coverage and time windows, so they should not be treated as one unified employment or productivity statistic. The source material does not provide a causal study linking AI adoption to job losses, wage changes or the labor-share decline.
Evidence to Watch Next
The next releases of productivity, employment, wages and business AI-use data will show whether the current pattern continues. Later revisions to national accounts and labor statistics may also change estimates for recent quarters. A sustained productivity increase alongside weak hours or hiring would strengthen the case that the relationship deserves close study, but would not by itself identify AI as the cause.
More direct evidence would compare outcomes at businesses adopting AI with those that do not, while accounting for differences in industry, investment and demand. For now, the confirmed development is a sizable gap between output growth and hours worked in the cited BLS index data. Whether AI explains a meaningful share of it—and whether workers will share in the resulting gains—remains unresolved.
Key Questions
How much did US business output and hours worked change?
In Meyer’s calculations from BLS indexes, nonfarm business output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked rose 0.9%. These are changes over that stated period, not a direct estimate of AI’s effect.
Do these figures prove AI is replacing workers?
No. They show output rising faster than hours worked, but do not identify the cause. AI may be one factor, but investment, business processes, industry shifts and other forces could also contribute.
What was the latest productivity growth reported in the analysis?
For the year to the second quarter of 2026, BLS figures cited by Meyer show nonfarm business productivity increasing 2.2%, as output grew 2.5% and hours worked rose 0.2%.
Which industries added or lost jobs?
In the 12 months to September, health care and social assistance added 520,000 jobs, while information industries lost 120,000, according to the figures in Meyer’s analysis. Total payrolls grew by 496,000 over the same 12-month period.
What evidence would clarify AI’s effect on jobs?
Researchers would need evidence that measures AI adoption and compares employment, hours, output and pay at adopting and non-adopting businesses while accounting for other differences. The aggregate figures currently cited do not provide that causal comparison.
Source: ThorstenMeyerAI.com
