🔍 Read the full analysis: The 80% Truth About AI Jobs on ThorstenMeyerAI.com
Get the latest gadgets delivered free with Prime
- Fast, free delivery on millions of items
- Prime Video, Amazon Music and more included
- Member-only deals all year
TL;DR
A November 9, 2026, article from ThorstenMeyerAI.com examines why services account for about four in five U.S. workers and how AI could affect that sector. It connects the trend to Baumol’s cost disease and cites a study in which an AI assistant increased customer-support agents’ issues resolved per hour by 15% on average. That result does not establish how many jobs AI will replace.
A November 9 article from ThorstenMeyerAI.com argues that about four in five U.S. workers are in services and that artificial intelligence could change productivity in this large part of the economy. The piece cites a study of 5,172 customer-support agents in which an AI assistant raised issues resolved per hour by 15% on average, while stressing that the result does not settle whether AI will reduce service-sector employment.
The article uses Baumol’s cost disease to explain why services can become more expensive even when productivity improves elsewhere. In work such as manufacturing, technology can allow each worker to produce more. In activities that depend on human time and attention—such as a live performance, a haircut, or some forms of care—there may be less scope to reduce the labor needed without changing the service itself.
Drawing on U.S. Bureau of Labor Statistics payroll data, the article reports that service-providing industries accounted for 62% of nonfarm payroll jobs in 1939, 72% in 1979 and 86% in 2025. Those figures exclude farm workers and self-employed people. Using a different measure that counts all workers, it cites International Labour Organization estimates putting the U.S. services share at 79.6% in 2025.
The article also compares official, quality-adjusted U.S. price changes since 2000: television prices fell 98%, while hospital services rose 274%, college tuition 188% and car repair 143%. The figures are presented as examples of diverging price trends, not proof that productivity alone caused each change. The source also notes that the United States spent 18.0% of its economy on health, compared with Germany’s 12.4%, indicating that national spending levels reflect more than the general pressures described by Baumol.
Infographic 02 · Baumol's cost disease
Why the workers moved to services
Baumol's mechanism in four steps, and what it looks like in US jobs.
- 1966Baumol and Bowen: the quartetA 45-minute Schubert quartet still takes about three hours of human work
- 1967Two kinds of workWhere labour is a tool, machines cut it again and again; where labour is the product, they can’t
- WagesPay rises everywhereTeachers, nurses and musicians must earn more too, or they leave
- ResultCosts rise, people moveIf we keep buying the same mix, more and more workers end up in the slow sector
Service industries, share of US nonfarm payroll jobs
US jobs, annual average 2025 (millions)
Payroll shares exclude farm workers and the self-employed (BLS establishment survey). Health spending: national health expenditure as a share of gross domestic product.
Sources: W. J. Baumol, “Macroeconomics of Unbalanced Growth”, American Economic Review 57(3), 1967, BLS Current Employment Statistics (own calculation of shares), CMS, National Health Expenditure, Table 1.
Powered by Thorsten Meyer AI
AI Meets a Service-Heavy Workforce
The issue matters because services already employ most U.S. workers. Even if AI has a substantial effect on only some jobs, changes in customer support, health care, education, administration and other service work could affect a large share of workers and businesses. The source’s central question is whether AI can raise productivity in work that has historically been harder to speed up without reducing the quality or personal attention people value.
The cited support-agent result points to a possible gain in output per hour, but it is not a forecast of economy-wide effects. Higher productivity might allow an organization to handle more requests, improve service, reduce staffing needs, or combine those outcomes. Which result follows will depend on how employers deploy the tools, the type of work involved and how demand changes.
Baumol’s framework also offers a reason that productivity gains in one part of the economy do not automatically make every service cheaper. If wages rise across sectors while some services still require substantial human time, their costs can keep rising relative to goods that become easier to produce. AI could alter that pattern in some tasks, but the article does not establish that it will eliminate the underlying pressure across services.
Popular right now
Samsung 65-Inch QN70FA Neo QLED 4K Smart TV with 8-Foot WireLogic Ruby Ultra High Speed HDMI Cable (2025)
Ninja Luxe Café Premier 3-in-1 Espresso Machine, Drip Coffee Maker, and Cold Brew Maker
Samsung 55-Inch Neo QLED 4K TV with WireLogic 8-Foot Ultra High Speed HDMI Cable
As an affiliate, we earn on qualifying purchases.
The Long Rise of Service Work
The article challenges the idea that service work grew only because factory employment declined. Its payroll series shows the service share rising from 62% in 1939 to 72% in 1979, the year U.S. manufacturing employment reached its cited peak, and continuing to 86% in 2025. The different 79.6% figure uses an all-worker measure, rather than nonfarm payroll jobs, so the two percentages should not be treated as competing estimates of the same statistic.
Economists William Baumol and William Bowen examined the finances of performing arts organizations in their 1966 book, Performing Arts: The Economic Dilemma. Baumol developed the broader productivity argument in a 1967 paper. A string quartet provides the illustration: a performance requires four musicians for about 45 minutes, or three hours of combined labor, and reducing that time could change the performance rather than simply make it more efficient.
The distinction is not absolute. The source notes that supermarkets and self-service changed the labor involved in retail, while transport improvements made it easier for a lecturer to reach audiences. The question for AI is whether it can similarly change tasks in service work—and whether those changes preserve what customers, patients or students expect from the service.
““Whether that empties the service sector or pushes people into what’s left is the question of this season.””
— ThorstenMeyerAI.com article
What the Productivity Study Cannot Show
The source reports a 15% average increase in issues resolved per hour among 5,172 customer-support agents using an AI assistant. It does not provide the study’s publication date, full methods, the range of results among agents, or details about how the measure was calculated. The figure should be read as a result for that study and task, not as a general estimate of AI’s effect on all service workers.
It is also unclear whether the reported productivity gain led to higher service quality, lower costs, changed staffing, or increased demand. The source does not supply evidence that the study’s outcome translates into job losses or job creation. Nor does it establish how much AI can change tasks that depend on physical presence, professional judgment or personal interaction.
The price comparisons and employment shares have their own limits. The employment percentages use different populations and data sources, while the price movements do not isolate the causes of each increase or decrease. The article presents them as context for the argument, not as proof that Baumol’s theory explains every price change.
Evidence Needed on Jobs and Services
The next step is to see whether the customer-support result holds across other workplaces and service occupations. Useful evidence would include the study’s methods and publication details, follow-up results, and measures of service quality alongside output per hour. Those details would help readers judge how broadly the reported 15% productivity gain applies.
For employment, the key developments to watch are how organizations change staffing, tasks, wages and service capacity after adopting AI. A rise in output per worker alone cannot show whether workers are displaced, reassigned or supported in handling more work. The source frames these possibilities as unresolved, and it gives no timeline for a broader labor-market outcome.
The article is part of “Work After Work,” Episode 7, in a series about how the economy is built. Its immediate contribution is a historical and economic framework for considering AI in services; the scale and distribution of AI’s effects on jobs remain open.
Key Questions
What is the 80% figure about?
It refers to an International Labour Organization estimate that 79.6% of U.S. workers were in services in 2025. The source also reports that services made up 86% of nonfarm payroll jobs that year, a different measure that excludes self-employed and farm workers.
What is Baumol’s cost disease?
It is an economic explanation for why costs can rise in work where productivity is difficult to increase, even as productivity improves in other industries. The theory highlights services that require substantial human time, such as live performance or personal care.
Did AI increase productivity in customer support?
The article cites a study of 5,172 support agents in which an AI assistant raised issues resolved per hour by 15% on average. The source does not provide enough study details to establish how broadly that result applies.
Does the study show that AI will eliminate service jobs?
No. A measured increase in issues resolved per hour does not, by itself, show what happens to staffing. The source says whether AI reduces service-sector jobs or shifts workers into other roles remains an open question.
Source: ThorstenMeyerAI.com
