🔍 Read the full analysis: Could AI Be Behind The US Output Rise? The Data Has Limits on ThorstenMeyerAI.com
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TL;DR
US business-sector output has risen far faster than hours worked since late 2022, and productivity growth is above its 2007–2019 pace. The figures are consistent with AI contributing, but they do not show that AI caused the increase: adoption remains limited and other explanations are possible.
US output has grown much faster than hours worked since the end of 2022, while hiring has been modest and productivity has risen above its pace in the years before the pandemic. The figures have renewed questions about whether artificial intelligence is changing the labor market, but official statistics do not establish that AI caused the productivity gains.
The Bureau of Economic Analysis’ 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 all contributed. Computers and software accounted for about a third of third-quarter growth, according to the source article’s reading of the BEA figures; that does not mean all of the contribution came from AI.
The Bureau of Labor Statistics reported that nonfarm business productivity rose 2.2% over the year to the second quarter of 2026. Output in that sector grew 2.5%, while hours worked increased 0.2%. The sector covers private businesses outside farming, not the entire economy. From the fourth quarter of 2022 to the second quarter of 2026, the source’s calculations from BLS indexes put output growth at 10.0% and hours growth at 0.9%.
Employment figures show a different side of the expansion. Payrolls increased by 496,000 in the 12 months to September, with health care and social assistance adding 520,000 jobs. The information sector lost 120,000 jobs and remained 12% below its November 2022 peak. Overall unemployment was 4.2%; it was 8.0% among people aged 20 to 24 and 7.0% among Black workers. These figures describe different parts of the labor market and do not, on their own, identify why hiring or employment changed.
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 Hiring
The gap between output and hours matters because productivity growth can support more economic output without an equivalent rise in labor hours. If sustained, faster productivity can increase the economy’s capacity to produce goods and services. But aggregate output does not show who benefits, which industries are gaining, or whether workers are sharing in the gains.
The source article 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 beginning in 1947. It also reports that real private-sector wages fell 0.6% over the year to September. Those measures add distributional concerns to the productivity story, although they do not prove that AI reduced workers’ share of income or caused wage declines.
For employers and workers, the distinction between a changing production process and a broader economic slowdown is important. Companies may be investing in software and equipment while hiring cautiously. Yet the same combination of output growth and weak job growth could have several explanations, from industry mix to post-pandemic adjustments. The data support scrutiny of the labor-market effects, not a settled verdict about the technology.
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What the Productivity Figures Measure
Productivity is output divided by hours worked. BLS’s nonfarm business measure excludes farms, government, nonprofits and households, so it is not a direct measure of output per worker across every part of the economy. The source article calculates that productivity grew about 2.1% a year from the end of 2019 to the second quarter of 2026, compared with 1.5% a year from 2007 to 2019.
The end of 2022 is often used as a reference point because ChatGPT launched on November 30 that year. The timing makes it possible to compare economic measures before and after the public arrival of generative AI, but a before-and-after comparison is not proof of cause. Technology adoption, investment and productivity can move on different timelines, and other economic changes occurred during the same period.
The source article also cites a Census Bureau survey from early October in which about one in four US businesses said it used AI. It notes that technology-sector jobs began shrinking before generative AI was in wide business use. The Financial Times’ October 31 opinion column, by John Burn-Murdoch, described the technology-sector employment picture as clearer than the wider labor-market picture. The source author says they could review only the column’s headline and summary, and the Wall Street Journal headline—not either article in full.
“Numbers can show that two things happen at the same time. They rarely show that one causes the other.”
— Thorsten Meyer, describing the limits of the economic data
The available figures do not isolate AI’s contribution to output or productivity growth. The source data show that computers and software contributed to economic growth and that a minority of surveyed businesses reported AI use; they do not show how much of the measured productivity increase came from AI, or whether adoption improved output per hour at those firms.
It is also unclear how much the employment trends reflect AI rather than other forces. Information-sector job losses began before widespread generative AI use, while payroll gains were concentrated in health care and social assistance. The figures cited here do not establish whether AI displaced workers, changed hiring plans, or affected wages. Nor do they settle whether the recent pace of productivity growth will continue.
Evidence Needed to Test the AI Link
The next evidence will come from updated productivity, employment and business-adoption data. BLS releases can show whether output and hours continue to diverge; payroll data can track which industries are adding or losing jobs; and Census surveys can indicate whether AI use is spreading among businesses. Each series answers a different question and should be read with its time period and coverage in view.
To identify a causal effect, researchers would need more than a national trend line. Firm- or industry-level evidence comparing AI adopters with similar non-adopters could help, particularly if it tracks output, hours, hiring and pay over time. Until such evidence is available, the most defensible conclusion is limited: US productivity has strengthened, but AI’s role in that rise—and its consequences for workers—remain unsettled.
Key Questions
Did AI cause the recent rise in US productivity?
The cited data do not establish that. They show faster productivity growth and some business use of AI, but do not measure how much AI contributed to the gains.
How much did US productivity grow?
BLS reported that nonfarm business productivity rose 2.2% over the year to the second quarter of 2026. Output rose 2.5% and hours worked rose 0.2% over that period.
Are jobs falling across the whole US economy?
No. Payrolls grew by 496,000 in the 12 months to September, according to the source article. Health care and social assistance added jobs, while the information sector lost 120,000.
What does the labor-share figure mean?
The labor share measures the portion of business output paid to workers as wages and benefits. The source article reports it at 52.8% in the second quarter of 2026, but that figure alone does not show what caused the decline.
Source: ThorstenMeyerAI.com
