🔍 Read the full analysis: More Output, Similar Hours: Exploring AI’s Role In US Growth on ThorstenMeyerAI.com
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TL;DR
US business-sector output rose 10.0% between the fourth quarter of 2022 and the second quarter of 2026, while hours worked increased 0.9%, according to calculations from BLS indexes cited by ThorstenMeyerAI.com. Productivity and GDP growth are strong, but the figures do not establish that AI caused the change or explain how its gains are distributed.
US business output rose 10.0% from the fourth quarter of 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 a November 1 analysis by ThorstenMeyerAI.com. The figures show a sharp rise in output per hour, but do not establish that artificial intelligence caused it or that productivity gains are responsible for weak hiring in some industries.
The latest figures in the analysis point to growth alongside limited expansion in labor hours. The Bureau of Economic Analysis’ advance estimate put real GDP growth at a 3.4% annual rate in the third quarter of 2026, up from 2.2% in the second quarter. Separately, BLS data for the nonfarm business sector show output grew 2.5% over the year to the second quarter, while hours worked rose 0.2%; productivity increased 2.2% over that period.
The longer comparison is calculated from BLS indexes rather than presented as a single official year-over-year rate: from the end of 2022 to the second quarter of 2026, output rose 10.0% and hours worked rose 0.9%. The analysis calculates that productivity grew about 2.5% a year over that span. It also reports average annual productivity growth of 2.1% since the end of 2019, compared with 1.5% from 2007 to 2019.
Employment and pay figures give a more uneven picture. Payrolls increased by 496,000 in the 12 months to September, according to the analysis, with health care and social assistance adding 520,000 jobs. Information industries lost 120,000 jobs over the same period. The analysis also cites a 52.8% labor share in the second quarter—the share of business output paid as wages and benefits—and a 0.6% fall in real private-sector wages 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 Pay
Higher output per hour can support economic growth without a matching increase in labor hours. That can benefit companies and consumers, but the figures cited here also raise questions about who receives the gains. A declining labor share and falling real private-sector wages suggest that output growth alone does not tell workers whether their purchasing power or share of business income is improving.
Employment totals can also obscure differences between groups. The analysis puts overall unemployment at 4.2%, compared with 8.0% among people aged 20 to 24 and 7.0% among Black workers. Those figures make the hiring slowdown particularly relevant to younger workers and groups facing higher unemployment. They do not, by themselves, show that AI is behind the gap.
For employers, the evidence is a reason to monitor productivity and workforce outcomes together, not to assume that any productivity increase came from AI. For workers and policymakers, the distinction matters: a technology-driven productivity gain would have different implications from growth caused by investment cycles, changes in demand or other economic forces.
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What the Output Measures Show
The analysis draws on data from the BLS, BEA, Census Bureau, Federal Reserve and Eurostat. BLS productivity statistics cover the nonfarm business sector: private businesses other than farms. They do not cover government, nonprofits or households. Productivity is output divided by hours worked, so it can rise when output grows faster than hours; the measure does not identify what caused that change.
The analysis uses the launch of ChatGPT on November 30, 2022, as a reference point for comparing output and hours before and after the public arrival of generative AI. That timing is useful for describing a pattern, but it is not a test of causation. The piece also notes that only about one in four US businesses reported using AI in early October, according to the Census Bureau, and that technology-sector employment began declining before generative AI was widely used in business.
The article cites recent opinion coverage from the Financial Times and The Wall Street Journal as part of the debate over productivity and employment. Its author says the full articles were not available to him and limits his description to the FT’s summary and the WSJ headline. The reported numerical comparisons are attributed to official statistical agencies or identified as the author’s calculations.
“Numbers can show that two things happen at the same time. They rarely show that one causes the other.”
— Thorsten Meyer, ThorstenMeyerAI.com
The main unresolved issue is causation. The output-hours comparison spans a period in which generative AI became more prominent, but it does not isolate AI’s effect from investment in computers and software, shifts in demand, business restructuring or other changes. The source analysis says computer and software investment contributed to third-quarter growth, but that alone does not establish how much of the increase came from AI.
The evidence on adoption is also limited: the analysis reports that about one in four US businesses said they used AI in early October, without establishing how frequently they used it, how many workers were affected, or whether use raised measured productivity. The supplied source ends partway through its discussion of the output-hours comparison and does not provide further evidence or a final causal conclusion. It is also unclear from the figures presented how much the wage and labor-share changes reflect AI rather than other economic factors.
Watching Hiring and Productivity
The next evidence will come from updated releases of GDP, productivity, payroll and wage data, alongside new Census Bureau measures of business AI use. Those releases can show whether output per hour continues to rise, whether hiring broadens beyond the sectors currently adding jobs, and whether real wages recover. They will not by themselves prove that AI caused a change; that would require evidence that separates AI adoption from other influences on output and employment.
For now, the figures support a measured conclusion: US output has grown much faster than hours worked over the period examined, and recent growth has coexisted with uneven job gains and pressure on real wages. Whether AI accounts for a substantial part of that pattern remains an open question.
Key Questions
How much did US business output and hours worked change?
In calculations from BLS indexes cited by ThorstenMeyerAI.com, business output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked rose 0.9%. These are changes over that specific period, not proof of what caused them.
Does the data prove AI is replacing workers?
No. The figures show changes in output, hours and employment, but do not isolate AI’s effect. The analysis notes that technology-sector job declines began before generative AI was widely used in business and says the broader labor-market picture is mixed.
What did the latest GDP estimate show?
The BEA’s advance estimate put real US GDP growth at a 3.4% annual rate in the third quarter of 2026, compared with 2.2% in the second quarter.
Are workers sharing in the growth?
The figures cited in the analysis point to pressure, but do not establish its cause: the labor share was 52.8% in the second quarter, and real private-sector wages fell 0.6% over the year to September. The labor share measures the portion of business output paid as wages and benefits.
Source: ThorstenMeyerAI.com
