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TL;DR
U.S. business-sector output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked increased 0.9%, according to calculations from BLS indexes cited by ThorstenMeyerAI.com. The figures point to faster productivity growth and uneven labor-market outcomes, but do not establish that AI caused either trend.
U.S. business-sector output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked increased 0.9%, according to calculations from Bureau of Labor Statistics indexes cited in a November 1 analysis by ThorstenMeyerAI.com. The gap points to faster productivity growth, but the figures alone do not show that artificial intelligence caused it, even as the economy expands with relatively modest hiring.
The broader economy grew at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter, according to the Bureau of Economic Analysis’ advance estimate released October 29. The BEA said investment, consumer spending and government spending all contributed to the increase. The analysis says computers and software accounted for about a third of third-quarter growth, much of it associated with AI investment; that attribution is the author’s account, not proof that AI itself raised economy-wide productivity.
For the nonfarm business sector, BLS data showed productivity grew 2.2% over the year to the second quarter of 2026. Output increased 2.5% in that period, while hours worked rose 0.2%. The sector measure covers private businesses other than farms and excludes government, nonprofits and households. The analysis calculates that productivity grew at an average annual rate of 2.1% from the end of 2019, compared with 1.5% from 2007 to 2019.
The labor-market picture is less buoyant. Payroll employment increased by 496,000 in the 12 months to September, while health care and social assistance added 520,000 jobs, according to the figures cited in the analysis. Information industries lost 120,000 jobs and remained 12% below their November 2022 peak. The analysis also reports that the labor share fell to 52.8% in the second quarter, its lowest level in the available series dating to 1947, and that 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.
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Productivity Gains, Uneven Payoffs
The gap between output and hours matters because it raises questions about who benefits from economic growth. Higher productivity can allow businesses to produce more without adding the same number of work hours. But the cited figures also show a labor market in which job gains are concentrated in a few areas, information-sector employment has declined, and real private-sector wages have fallen over the stated period.
The pressure appears sharper for some groups entering or seeking work. The analysis reports an overall unemployment rate of 4.2%, compared with 8.0% for people aged 20 to 24 and 7.0% for Black workers. Those rates were up from 5.5% and 4.8%, respectively, in April 2023. These comparisons describe different groups and periods; they do not by themselves establish why unemployment changed or prove that AI displaced workers.
For employers and workers, the central issue is not simply whether output per hour is rising. It is whether productivity gains lead to higher pay, more sustainable business growth, or fewer opportunities for particular workers. The data presented here show the uneven outcomes, but do not settle how much is due to technology, industry shifts, hiring decisions or other economic forces.
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The Post-2022 Productivity Comparison
The analysis uses the end of 2022 as a comparison point because ChatGPT launched on November 30, 2022, a date often used to mark the arrival of widely visible generative AI. From the fourth quarter of 2022 to the second quarter of 2026, its calculations from BLS indexes put output growth at 10.0% and hours-worked growth at 0.9%. Those figures imply productivity growth of about 9.1% over the period, or roughly 2.5% a year, according to the author’s arithmetic.
A coincident timeline is not a causal test. The analysis notes that about one in four U.S. businesses reported using AI in early October, based on Census Bureau data. It also says technology-sector jobs began declining before generative AI was in wide business use. That timing complicates any claim that AI alone explains either the productivity increase or job losses.
The article responds to public discussion of whether productivity gains offer evidence of AI’s labor-market effects. It references a Financial Times opinion column published October 31 and a Wall Street Journal headline published the following day, but says the full articles were behind paywalls. Its analysis instead draws on official data from the BLS, BEA, Census Bureau, Federal Reserve and Eurostat.
“Numbers can show that two things happen at the same time. They rarely show that one causes the other.”
— Thorsten Meyer, ThorstenMeyerAI.com
AI’s Causal Role Is Unsettled
The figures establish that output rose faster than hours worked over the periods cited. They do not identify what caused that gap. The analysis says the pattern is compatible with an AI explanation, but also with other factors; the available numbers do not isolate AI’s contribution from investment, changes in business practices, workforce composition or broader economic conditions.
There are limits to the evidence as presented. The 10.0% output and 0.9% hours figures are the author’s calculations from BLS indexes, while the third-quarter GDP figure is an advance estimate and may be revised. The source material does not provide enough detail to determine how many jobs were lost specifically because of AI, whether gains in output will translate into higher wages, or whether the reported labor-share decline will persist.
The analysis also reports that hiring is slow while layoffs remain low, but the supplied material does not give specific hiring or layoff rates to quantify those descriptions. Its reference to European employment and productivity as a contrast is not accompanied by figures here, so the comparison cannot be assessed from the information provided.
Watch Revisions and Labor Data
The next useful evidence will come from updated BEA GDP estimates and subsequent BLS productivity, employment, hours and wage releases. Revisions could change the reported pace of recent growth. Tracking the same measures over time can also show whether productivity gains persist and whether hiring and real wages begin to reflect them.
Further Census Bureau reporting on business AI use may help clarify how widely companies are adopting the technology, but adoption rates alone will not measure its effect on jobs or output. Establishing that connection requires evidence that separates AI’s contribution from other changes in investment, demand and business operations. Until then, the data support a report of strong output growth and uneven labor-market conditions, not a definitive account of AI’s impact.
Key Questions
What does the 10% figure measure?
It is the analysis author’s calculation from BLS indexes: nonfarm business-sector output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026. It is not a measure of GDP growth over that same period.
Does the data prove AI caused productivity to rise?
No. The figures show output growing faster than hours worked, but they do not isolate AI’s effect or establish that AI caused the productivity increase.
What happened to U.S. employment in the year to September?
Payrolls grew by 496,000 jobs over the 12 months to September, according to figures cited by the analysis. Health care and social assistance added 520,000 jobs, while information industries lost 120,000.
How did wages and the labor share change?
The analysis reports that real private-sector wages fell 0.6% over the year to September. It also says the labor share was 52.8% in the second quarter, the lowest in the series dating to 1947.
What evidence could clarify AI’s role?
Future productivity and employment data, alongside more detailed reporting on business AI adoption and its effects on work, could help. The evidence would need to distinguish AI’s contribution from other economic changes.
Source: ThorstenMeyerAI.com
