🔍 Read the full analysis: The US Made 10% More With Similar Hours. What Can AI Explain? on ThorstenMeyerAI.com
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TL;DR
US nonfarm business 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 Bureau of Labor Statistics indexes cited by Thorsten Meyer. Productivity has accelerated, but the available data do not show that AI caused the change or explain how much it contributed.
US business output rose 10.0% from late 2022 to the second quarter of 2026, while hours worked increased just 0.9%, according to calculations from Bureau of Labor Statistics indexes cited in an analysis by Thorsten Meyer. The figures point to a substantial productivity gain, but they do not establish that artificial intelligence caused it, even as weak hiring and uneven wage and employment outcomes sharpen questions about who benefits from growth.
The latest quarterly figures show both a fast-growing economy and a relatively small increase in labor input. The Bureau of Economic Analysis’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, according to the BEA.
For the nonfarm business sector, the BLS reported that productivity rose 2.2% over the year to the second quarter of 2026. Output increased 2.5% over that period, while hours worked rose 0.2%. Meyer’s longer comparison, calculated from BLS indexes, puts output growth at 10.0% and hours growth at 0.9% between the fourth quarter of 2022 and the second quarter of 2026. The figures describe output per hour; they do not identify what caused the increase.
The labor-market picture is mixed. Payrolls grew 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 positions and remained 12% below their November 2022 peak. The analysis also reports that the labor share of business output fell to 52.8% in the second quarter, while real private-sector wages fell 0.6% over the year to September.
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, Uneven Payoffs
Higher output per hour can support economic growth without requiring businesses to add the same proportion of work hours. But aggregate productivity figures do not show whether the gains are reaching workers through higher pay, more hiring or improved working conditions. The source analysis reports that real private-sector wages declined 0.6% over the year to September and that labor’s share of business output reached 52.8%, its lowest level in the recorded series dating to 1947.
Employment changes also differ sharply by industry and age. The source reports overall unemployment at 4.2%, compared with 8.0% for people aged 20 to 24 and 7.0% for Black workers. Those figures do not, by themselves, show that AI is responsible for weaker prospects among younger workers or for the decline in information-sector jobs. They do show why a strong headline growth rate can coexist with concern about access to jobs and the distribution of income.
For businesses and policymakers, the central question is not simply whether productivity is rising. It is whether the improvement lasts, what drives it, and how its benefits are shared. The figures offer a timely measure of output and labor input, but not a causal test of AI’s economic effects.
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The Post-2022 Productivity Comparison
The fourth quarter of 2022 is used in the analysis as a reference point because ChatGPT launched on November 30, 2022. That makes the period useful for tracking what happened after generative AI became widely visible, but the date is not an experiment that isolates AI from other changes in the economy. Output, employment and productivity can be affected by investment, demand, business restructuring, technology other than AI and shifts in the kinds of firms or workers included in the data.
The BLS productivity measure cited here covers the nonfarm business sector: private businesses, excluding farms. It does not cover government, nonprofits or households. The annual comparison also shows a faster pace than in the earlier period cited by Meyer: productivity grew 2.1% a year from the end of 2019, compared with 1.5% a year from 2007 to 2019. These are different time windows, and they do not establish which technologies or economic forces account for the gap.
Meyer’s analysis follows two recent opinion headlines: a Financial Times column on whether productivity and employment trends could offer evidence of AI’s labor-market impact, and a Wall Street Journal headline about economic growth that is not shared equally. He says he could access the Financial Times headline and summary and the Journal headline, but not both articles in full. His reported data analysis is based on official statistics from the BLS, BEA, Census Bureau, Federal Reserve and Eurostat.
The data cited do not establish how much, if any, of the productivity increase was caused by AI. The source analysis says only about one in four US businesses reported using AI in an early-October Census Bureau survey, but it does not provide further detail here on what counted as use, how intensively businesses used the tools, or whether adoption changed their output or staffing.
The timeline also complicates a direct link: the analysis says technology employment began falling before generative AI was in wide business use. Meanwhile, the source reports that computer and software investment accounted for about a third of third-quarter growth, much of it associated with the AI build-out. Investment activity may support growth, but it is not proof that AI tools have raised productivity across businesses or caused job losses.
Other details remain uncertain. The source gives a payroll total for the year to September and industry changes, but these figures alone do not show whether employers are replacing workers with automation, slowing hiring for other reasons or responding to shifts in demand. The available material also does not provide a direct measure linking individual firms’ AI adoption to their output, hours or wages.
Upcoming Jobs and Productivity Data
The next evidence will come from updated official releases on productivity, payrolls, wages and business technology use. Those measures can show whether the recent pattern persists, whether hiring broadens beyond health care and social assistance, and whether pay begins to track output growth more closely. Comparisons should keep their stated periods and baselines: a single quarterly estimate can be revised, and different measures cover different parts of the economy.
To assess AI’s role, researchers and policymakers will need more than a before-and-after comparison. Firm-level evidence that tracks adoption alongside output, hours, hiring and pay would help distinguish AI’s contribution from other causes. Until such evidence is available, the confirmed development is a productivity increase alongside modest hours growth and uneven labor-market outcomes—not proof that AI produced those results.
Key Questions
How much did US output and hours worked change?
In calculations from BLS indexes cited by Meyer, nonfarm business output rose 10.0% and hours worked rose 0.9% from the fourth quarter of 2022 to the second quarter of 2026. The comparison does not identify the cause of the difference.
Does the productivity data prove AI is replacing workers?
No. The figures show output, hours and employment trends, but they do not isolate AI’s effect. The source analysis says technology-sector jobs were already declining before generative AI was in wide business use.
What was the latest reported GDP growth rate?
The BEA’s advance estimate put real US GDP growth at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter. The estimate is subject to revision.
Were jobs growing across all industries?
No. The source analysis reports 496,000 additional payroll jobs over the 12 months to September, including 520,000 added in health care and social assistance. Information industries lost 120,000 jobs over the same period.
What evidence would clarify AI’s effect?
Evidence linking individual businesses’ AI adoption to changes in output, work hours, hiring and pay would help distinguish AI’s effects from broader economic changes. The figures cited here do not provide that firm-level comparison.
Source: ThorstenMeyerAI.com
