🔍 Read the full analysis: The AI Productivity Debate Through The Lens Of US Work Hours on ThorstenMeyerAI.com
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TL;DR
US 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 Bureau of Labor Statistics indexes cited by ThorstenMeyerAI.com. The figures sharpen debate over whether AI is changing employment, but they do not establish that AI caused the productivity gains or slower hiring.
US 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 Bureau of Labor Statistics indexes analyzed by ThorstenMeyerAI.com. The gap has revived debate over whether artificial intelligence is raising productivity while limiting hiring, but the figures alone do not show that AI caused the change.
The report, published November 1 by Thorsten Meyer, puts the long-run comparison alongside newer economic data. BLS figures show nonfarm business productivity grew 2.2% over the year to the second quarter of 2026, as output increased 2.5% and hours worked rose 0.2%. The nonfarm business measure covers private businesses other than farms, not government, nonprofits or households.
The broader economy was still growing. The Bureau of Economic Analysis’ advance estimate put third-quarter real GDP growth at a 3.4% annual rate, up from 2.2% in the second quarter. Separately, payrolls grew by 496,000 in the 12 months to September, the report says. Health care and social assistance added 520,000 jobs over that period, while information industries lost 120,000 and remained 12% below their November 2022 employment peak.
The report also highlights uneven outcomes for workers. It says real private-sector wages fell 0.6% over the year to September, while the labor share—the portion of business output paid as wages and benefits—was 52.8% in the second quarter, its lowest level in the series beginning in 1947. Overall unemployment was 4.2%; the reported rate was 8.0% for people aged 20 to 24 and 7.0% for Black workers.
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 figures matter because output can expand without a comparable increase in working hours, changing what economic growth means for hiring and pay. Higher productivity can allow businesses to produce more with the same labor input. But the aggregate numbers do not show which firms or workers benefited, whether reduced hours reflect automation, or whether workers’ earnings rose alongside output.
The report describes hiring as slow while layoffs remain low, a combination that may be difficult for people entering the workforce. It cites unemployment of 8.0% among 20- to 24-year-olds, compared with 4.2% overall. Those figures do not establish that AI has caused the difference, but they underline why the distribution of gains—and access to new jobs—matters beyond headline GDP growth.
For employers and policymakers, the distinction between productivity growth and AI-driven productivity growth is consequential. If AI is responsible, businesses may be changing how work is organized; if other forces are driving the gains, attributing labor-market shifts to AI could misstate what is happening. The available figures describe a pattern, not a causal finding.
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The Post-2022 Productivity Comparison
The report uses the launch of ChatGPT on November 30, 2022 as a convenient marker for comparing the period before and after generative AI became widely discussed. Meyer’s calculation from BLS indexes finds output up 10.0% and hours worked up 0.9% between the fourth quarter of 2022 and the second quarter of 2026. That timing is relevant to the debate, but it does not prove that AI produced the change.
Longer-term figures also show productivity growth running faster than in the preceding period: the report says productivity grew 2.1% a year from the end of 2019, compared with 1.5% annually from 2007 to 2019. The BLS’ year-over-year reading for the second quarter of 2026 was 2.2%. These are different time windows, so they describe related but not interchangeable measures.
Business adoption remains incomplete. The report cites early-October Census Bureau data showing about one in four US businesses reported using AI. It also notes that technology-sector employment began declining before generative AI was in wide business use, complicating claims that AI alone explains job losses.
“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 Role Remains Unproven
The central unknown is how much, if any, of the productivity increase is attributable to AI. The report draws on official statistics and compares output and hours across time, but those measures do not isolate AI from other influences such as investment, business restructuring or changes in demand. Meyer says the pattern is compatible with an AI explanation, but also with other explanations.
The adoption figure is not evidence that one in four businesses uses AI intensively or that the technology has raised their output; it is a reported use measure, and the source material does not provide further detail about usage or effects. The report also does not establish why real wages declined or why employment outcomes differ by age and race. Its figures describe the period and groups cited, not the causes of those outcomes.
More Data Needed on Adoption
The next useful evidence will be further quarterly productivity, hours, wage and employment releases, alongside clearer measures of how businesses use AI and whether adoption changes output or staffing. Those data could help test whether the post-2022 pattern persists and whether it is concentrated in particular sectors.
For now, the reported figures establish a substantial gap between business output and hours worked since late 2022, as well as uneven hiring and wage trends. They leave open whether AI is a major driver, a minor contributor or largely unrelated to the changes. Readers should treat the connection as a live economic question, not a confirmed causal conclusion.
Key Questions
What is the main finding in the report?
BLS indexes cited by ThorstenMeyerAI.com show business-sector output rose 10.0% from the fourth quarter of 2022 to the second quarter of 2026, while hours worked rose 0.9%.
Does the data prove AI is replacing workers?
No. The data show output, hours and employment changing over overlapping periods, but do not establish that AI caused those changes or that it replaced workers.
What was US economic growth in the third quarter of 2026?
The BEA’s advance estimate put real GDP growth at a 3.4% annual rate in the third quarter, compared with 2.2% in the second quarter.
Which sectors added or lost jobs?
In the 12 months to September, health care and social assistance added 520,000 jobs, while information industries lost 120,000, according to figures cited in the report. Total payrolls grew by 496,000 over that period.
How widespread was reported business use of AI?
The report cites early-October Census Bureau figures saying about one in four US businesses reported using AI. That measure does not by itself establish how intensively businesses used it or what effect it had on productivity.
Source: ThorstenMeyerAI.com
