🔍 Read the full analysis: US Growth Without More Work: Exploring The AI Hypothesis on ThorstenMeyerAI.com
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TL;DR
U.S. business output has increased much faster than hours worked since late 2022, and recent productivity growth is above the rate recorded from 2007 to 2019. The pattern is consistent with AI contributing, but official data do not establish that AI caused it; employment and wage pressures are also uneven.
U.S. economic output is growing much faster than the amount of labor used to produce it, but the latest figures do not show that artificial intelligence is the cause. An analysis published November 1 by ThorstenMeyerAI.com, drawing on federal statistics, says business-sector output rose 10.0% from the end of 2022 through the second quarter of 2026, while hours worked increased 0.9%—a gap that matters for jobs and pay, but has several possible explanations.
The Bureau of Economic Analysis (BEA) estimated that U.S. real gross domestic product grew at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter. The BEA said investment, consumer spending and government spending all contributed. That broad measure of economic growth does not, by itself, reveal how much of the gain came from AI or how widely households shared in it.
For the nonfarm business sector, the Bureau of Labor Statistics (BLS) reported that output grew 2.5% over the year through the second quarter of 2026, while hours worked rose 0.2%. Productivity—output per hour—was up 2.2% over that year. The source analysis calculates that, from the fourth quarter of 2022 to the second quarter of 2026, output rose 10.0% and hours 0.9%, implying productivity growth of about 2.5% a year over that period.
The analysis also describes uneven labor-market conditions. Payrolls increased by 496,000 in the 12 months through September, while health care and social assistance added 520,000 jobs. Information industries lost 120,000 jobs and remained 12% below their November 2022 peak, according to the figures cited. The source says real private-sector wages fell 0.6% over the year to September and the labor share of business output was 52.8% in the second quarter, a record low in the series that began in 1947.
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.
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Productivity Gains Meet Uneven Jobs
The gap between rising output and nearly flat hours is important because productivity growth can support higher living standards if its gains reach workers through pay, better services or lower prices. The figures presented in the analysis, however, show that strong aggregate growth has not meant uniformly strong hiring or wage gains. The reported decline in labor’s share of business output and in real private-sector wages points to a distribution question as well as a production question.
Conditions also vary by age and race. The source reports unemployment of 8.0% for people aged 20 to 24 and 7.0% for Black workers, compared with an overall rate of 4.2%. Those figures do not establish why unemployment differs, but they underscore that a strong headline growth rate can coexist with greater difficulty for some groups entering or remaining in work.
For employers and policymakers, the distinction between productivity improvement and AI-driven productivity matters. If AI is a major cause, decisions about training, hiring and how gains are shared may need to account for faster changes in how work is organized. If other factors explain much of the productivity increase, attributing it to AI could lead to mistaken conclusions about workers and investment.
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What the Productivity Figures Measure
Productivity is calculated as output divided by hours worked. The BLS measure cited here covers the nonfarm business sector: private businesses, excluding farms, and not government, nonprofits or households. It is not a direct measure of AI adoption, nor does it show which technologies or workplace changes produced a change in output per hour.
The analysis compares recent productivity with earlier periods. It reports average annual growth of 2.1% from the end of 2019, versus 1.5% from 2007 to 2019. It also uses the launch of ChatGPT on November 30, 2022, as a marker for comparing before and after the public arrival of widely used generative AI tools. That is a date for comparison, not evidence that AI adoption began then or caused subsequent economic changes.
Two recent media developments prompted the discussion. A Financial Times opinion column on October 31 asked whether the labor-market data were the first clear evidence of AI’s impact. The following day, The Wall Street Journal published a headline about an economy advancing without bringing everyone along. ThorstenMeyerAI.com says it could access the FT headline and summary and the WSJ headline, but not either full article; its analysis therefore relies on publicly available government statistics rather than a full review of those arguments.
The data show productivity growth alongside limited growth in hours worked; they do not identify how much, if any, of that change came from AI. The source cites an early-October Census Bureau finding that about one in four U.S. businesses used AI, but that figure does not specify how intensively firms used it or whether use increased their output or reduced labor needs.
The analysis says information-sector employment began declining before generative AI was in wide business use. It also notes that the same broad pattern could reflect factors other than AI. The supplied figures do not separate the effects of automation, investment in computers and software, changes in demand, business restructuring or other forces. The reported wage, labor-share and employment figures are descriptive; they do not establish a single cause.
There are also limits to the comparisons. The 10.0% output and 0.9% hours figures cover the fourth quarter of 2022 through the second quarter of 2026 and are the source author’s calculations from BLS indexes. The third-quarter GDP figure is an advance estimate, while the employment and productivity measures cover different periods and populations. How much growth workers will ultimately share, and whether the recent productivity pace will continue, remain unsettled.
The Next Data to Watch
The next evidence will come from updated BLS productivity, employment and wage releases, along with BEA revisions to GDP estimates. These can show whether the recent gap between output and hours persists, narrows or widens, but they will not alone isolate AI’s contribution.
More direct evidence would require data linking firms’ AI adoption to measurable changes in output, staffing and pay over time, while accounting for other differences between businesses. The Census Bureau’s business-use measures may help track adoption, but use alone does not demonstrate economic impact. For now, the published figures support a report of strong growth, faster productivity and uneven labor conditions—not a settled conclusion that AI is producing growth without more work.
Key Questions
Is AI proven to be behind the recent U.S. productivity increase?
No. The figures show productivity growth and relatively little growth in hours worked, but they do not identify AI as the cause. Other economic and business changes may also explain the pattern.
How much did output and hours worked change after late 2022?
According to the source author’s calculations from BLS indexes, business-sector output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked increased 0.9% over the same period.
Was the U.S. economy shrinking in the third quarter of 2026?
No. The BEA’s advance estimate put real GDP growth at a 3.4% annual rate in the third quarter, up from 2.2% in the second quarter. GDP growth does not mean every industry or worker experienced the same gains.
What happened to U.S. jobs over the year through September?
The source reports payroll growth of 496,000 over 12 months. Health care and social assistance added 520,000 jobs, while information industries lost 120,000. These figures describe different sectors and do not establish that AI caused the losses.
What evidence could clarify AI’s effect on employment?
Researchers would need evidence connecting firms’ AI adoption to changes in output, hiring, hours and pay over time, while accounting for other factors. Government releases can track broad trends, but the figures cited so far do not isolate AI’s effects.
Source: ThorstenMeyerAI.com
