🔍 Read the full analysis: The US Grew 10% With Similar Hours. What Might AI Have To Do With It? on ThorstenMeyerAI.com
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TL;DR
US nonfarm business output rose 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. Productivity growth has accelerated, but the figures do not establish that AI caused the change; adoption remains limited and other explanations are possible.
US business 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 using Bureau of Labor Statistics indexes. The gap points to faster productivity growth, but it does not show that artificial intelligence caused it; available data also show limited reported business adoption and cannot isolate AI’s effect from other forces.
The latest economic data present a mixed picture: output and productivity are growing, while hiring is subdued and gains are uneven across industries. The Bureau of Economic Analysis said real GDP grew at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter. That GDP measure covers the broader economy and should not be confused with the BLS business-sector productivity figures.
For the nonfarm business sector, BLS data show output grew 2.5% over the year to the second quarter, while hours worked rose 0.2%; productivity increased 2.2%. Since the end of 2019, productivity has grown at an annual average rate of 2.1%, compared with 1.5% from 2007 to 2019. The longer-run comparison suggests an improvement, but it does not identify what caused it.
Employment numbers add to the puzzle. Payrolls increased by 496,000 in the 12 months to September, with health care and social assistance adding 520,000 jobs. Information industries lost 120,000 jobs and stood 12% below their November 2022 peak. Those sector-specific figures do not mean the economy lost jobs overall: they show that employment growth was concentrated elsewhere.
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
If businesses can produce more without adding many work hours, the change could affect hiring, wages and the distribution of income. But productivity growth alone does not determine who benefits. The source material reports the labor share of business output at 52.8% in the second quarter, its lowest level since records began in 1947, and real private-sector wages down 0.6% over the year to September. These figures point to pressure on workers’ share of output, although they do not establish that AI caused the decline.
Job seekers may feel the change unevenly. Overall unemployment was 4.2%, compared with 8.0% for people aged 20 to 24 and 7.0% for Black workers, according to the supplied figures. The data describe different outcomes across groups; they do not by themselves explain why those gaps exist. A period of strong aggregate growth can therefore coexist with slower entry-level hiring and weak wage growth.
For companies, the issue is whether new tools raise output per worker enough to alter staffing plans, and whether those gains persist. For workers and policymakers, the important question is how productivity gains reach pay and employment. The current evidence makes those questions more pressing, but it cannot yet give AI a precise share of the answer.
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The Post-2022 Productivity Comparison
The fourth quarter of 2022 is used here as a reference point because ChatGPT launched on November 30, 2022, making it a convenient marker for the public arrival of generative AI. The source author’s calculation from BLS indexes finds output up 10.0% and hours up 0.9% between that quarter and the second quarter of 2026. The figures describe a period that overlaps with wider AI development; they do not show that the technology produced the measured change.
Two recent opinion pieces helped put the question in public view. A Financial Times column by John Burn-Murdoch asked whether the data were the first clear evidence of AI’s labor-market impact, while a Wall Street Journal headline described an economy advancing without taking everyone along. The source author says the full articles were behind paywalls and relies instead on BLS, BEA, Census Bureau, Federal Reserve and Eurostat data. The reported summaries and headlines are not evidence of the underlying claims.
The source also reports that only about one in four US businesses said it used AI in early October, based on Census Bureau data. That measure indicates adoption was not universal; it does not capture how intensively firms used AI, whether they used it indirectly through vendors, or how much it changed productivity. The source notes that information-sector job losses began before generative AI was widely used in businesses, another reason to avoid a simple cause-and-effect conclusion.
The central unknown is how much of the productivity increase is attributable to AI. National output and hours-worked statistics measure economic activity, not the contribution of a particular technology. The period also includes other potential influences, such as investment, changes in business processes and shifts in which industries are expanding. The supplied figures do not quantify those effects or separate them from AI adoption.
Adoption data are also limited: the reported Census measure says about one in four businesses used AI in early October, but the source provides no detail here on the survey’s exact definition, intensity of use or resulting productivity gains. Nor do the available numbers establish that AI explains the labor share, wage or unemployment patterns. The source describes Europe as showing a contrasting pattern of more jobs and flat productivity, but gives no comparable figures in the provided material to assess that comparison.
Some measurements are preliminary or cover different periods and populations. BEA’s third-quarter GDP growth rate is an advance estimate; BLS productivity figures cited here run through the second quarter. The figures therefore should not be combined as if they were one measure covering the same period.
Watch Adoption and Revised Data
The next evidence will come from later releases of productivity, output, hours and employment data, along with revisions to the advance GDP estimate. Those updates can show whether the recent pace persists, but they will not by themselves prove AI caused it. A stronger case would require evidence linking businesses’ AI use to measured changes in output, hours, hiring or pay, while accounting for other changes in those firms.
Readers should also watch whether AI adoption spreads beyond the businesses currently reporting use, and whether productivity gains appear across industries rather than being concentrated in a few. Employment and wage data will help show whether the expansion reaches workers, including younger people and groups with higher unemployment in the figures cited here. For now, the confirmed development is a wide gap between output growth and hours worked; its cause and distribution remain unsettled.
Key Questions
Did US output really rise 10% while hours worked rose just 0.9%?
Those are the source author’s calculations from BLS indexes for the nonfarm business sector, comparing the fourth quarter of 2022 with the second quarter of 2026. They are not the same measure as overall GDP.
Does the data prove AI caused the productivity increase?
No. The figures show that output rose much faster than hours worked, but they do not isolate AI’s contribution. Correlation over the same period is not proof of cause, and other business and economic changes may also matter.
Is the US economy losing jobs overall?
The supplied figures do not show an overall payroll decline. Payrolls grew by 496,000 over the 12 months to September, although information industries lost 120,000 jobs and hiring was described as slow.
How widespread is business use of AI?
The source reports that about one in four US businesses said it used AI in early October, citing the Census Bureau. That figure does not say how intensively AI was used or whether it raised productivity.
What should readers watch next?
Later releases on productivity, employment, wages and AI adoption will show whether the pattern continues. More direct firm-level evidence is needed to connect AI use to changes in output or staffing.
Source: ThorstenMeyerAI.com
