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TL;DR
A November 9, 2026, article traces the growth of US service employment and explains why some services remain costly even as factory productivity rises. It points to a study of 5,172 customer-support agents in which an AI assistant increased issues resolved per hour by 15% on average, while leaving open whether such tools will reduce service-sector jobs or change the work people do.
A November 9 report from ThorstenMeyerAI.com argues that the US shift toward service work began decades before manufacturing employment peaked in 1979, and examines how artificial intelligence could affect industries where human time is a large part of the service. The article cites a study of 5,172 customer-support agents in which an AI assistant raised issues resolved per hour by 15% on average, but says the broader effect on service-sector employment remains uncertain.
The report’s employment figures show that service-providing industries accounted for 62% of US nonfarm payroll jobs in 1939, 72% in 1979 and 86% in 2025. Those figures use Bureau of Labor Statistics payroll data and exclude farm workers and self-employed people. Using a broader measure that counts all workers, the International Labour Organization estimated that 79.6% of US workers were in services in 2025—about four in five.
The article uses Baumol’s cost disease to explain why service prices can rise even as productivity improves elsewhere. Economist William Baumol’s framework distinguishes work where technology can produce more output with less labor from work where human time is central to the product, such as live music, teaching or personal medical care. The report says wages tend to rise across both types of work, even when productivity gains are uneven.
As examples of diverging prices, the article reports that since 2000 the official, quality-adjusted price of a television fell by 98%, while hospital services rose 274%, college tuition 188% and car repair 143%. These comparisons illustrate different price trends; they do not establish that Baumol’s theory alone caused each increase. The report also notes that US healthcare spending was 18.0% of the economy, compared with Germany’s 12.4%, underscoring that policy and institutional choices affect costs too.
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.
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AI Meets Labor-Intensive Services
The development matters because services account for the large majority of US employment, while many of their costs are tied to labor that is difficult to replace or compress. If AI helps workers handle more cases, it could change the productivity equation in areas such as customer support. The cited result offers evidence of a measurable gain in one setting, not proof that AI can deliver the same improvement across healthcare, education, repair work or other services.
The report frames the central economic question as whether productivity tools will reduce the number of people needed for service work or allow employees to handle more demand while shifting human effort to tasks that still require judgment and personal attention. The answer matters to workers, employers and customers: it could affect job duties, staffing, service capacity and prices. The article does not provide evidence that the study’s average gain led to lower costs for customers or fewer jobs.
The cost comparisons also caution against treating rising service prices as the result of a single cause. The report points to haircuts and car repairs as examples of services whose prices rose without health insurers or student loans, but contrasts US and German healthcare spending to show that national systems can produce different overall costs. Productivity is part of the explanation, not a complete account of every bill.
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From Orchestras to Economic Theory
The report traces Baumol’s argument to research by William Baumol and William Bowen on performing arts, published in their 1966 book, Performing Arts: The Economic Dilemma. They observed that a string quartet still requires the same number of musicians and playing time even when manufacturing methods can sharply reduce the labor needed to make a product. The report quotes their example of a 45-minute Schubert quartet requiring roughly three person-hours of performance.
In a 1967 paper, Baumol extended the idea to the wider economy. Some work, he argued, allows cumulative productivity gains through machines, scale or new methods. In other work, the labor itself is central to what customers receive. The distinction is not absolute: the report notes that technology and organizational changes can improve productivity in parts of service industries, including retail and transport.
The article connects that framework to the longer employment shift. Manufacturing employment reached nearly 20 million in June 1979, according to the report, but service employment had already grown substantially before that peak and continued to do so afterward. The pattern suggests the rise of services was not simply a consequence of factory jobs shrinking.
“Whether that empties the service sector or pushes people into what’s left is the question of this season.”
— The ThorstenMeyerAI.com report
AI’s Employment Effects Remain Open
The source report does not identify the customer-support study’s authors, publication date, research setting or methods. It gives the sample size—5,172 agents—and an average increase of 15% in issues resolved per hour, but does not say how results varied among workers or how long the effect lasted. It is therefore not possible from the supplied material to assess how broadly the result applies.
It is also unclear whether the productivity gain changed staffing levels, pay, customer satisfaction, wait times or costs. A higher number of cases resolved per hour does not, by itself, show that jobs were eliminated or that service became cheaper. The report does not provide comparable evidence for AI use across other service industries.
The employment and price figures have limits as well. The BLS payroll series excludes self-employed and farm workers, while the ILO estimate uses a broader worker population. The article’s price comparisons describe changes since 2000, but the supplied material does not detail the full methodology or isolate the causes of each increase. Its figures should not be read as proof that one theory explains all service prices.
Evidence Needed Beyond Customer Support
The next development to watch is whether independent research and workplace data show similar productivity gains in other service occupations. Useful evidence would compare output and service quality before and after AI adoption, while tracking effects on staffing, wages, customer outcomes and costs over time. The report does not name a forthcoming study or policy milestone.
For now, the cited customer-support result is a specific finding, not a forecast for the whole economy. The broader question posed by the report—whether AI reduces labor demand or changes the tasks workers perform—will depend on how employers deploy these tools and whether productivity gains translate into more service, lower prices, different jobs or some combination of those outcomes.
Key Questions
What is the main development in the report?
The November 9 report connects the long rise of US service employment with Baumol’s cost disease and considers how AI might raise productivity in service work. It cites a customer-support study that found a 15% average increase in issues resolved per hour among 5,172 agents using an AI assistant.
Does the report say that four in five US workers are in services?
Yes, using the International Labour Organization’s estimate: services accounted for 79.6% of US workers in 2025. A separate BLS payroll measure put service-providing industries at 86% of nonfarm payroll jobs, but excludes farm workers and self-employed people.
What does Baumol’s cost disease mean?
It describes how labor-intensive services can become more expensive relative to goods when productivity grows faster in other industries. Wages may rise across the economy, while activities centered on human time—such as live performance or personal care—can be harder to speed up without changing the service.
Does the 15% result show that AI will eliminate customer-support jobs?
No. The reported measure is issues resolved per hour, not job losses. The source does not provide evidence about staffing, pay or longer-term employment effects, and it does not establish that the result applies to other service industries.
Why did some service prices rise while television prices fell?
The report uses the contrast to illustrate uneven productivity and price trends: it says the quality-adjusted price of televisions fell 98% since 2000, while hospital services, college tuition and car repair rose. The figures do not show that productivity differences alone caused each price change; policy, institutions and other factors also matter.
Source: ThorstenMeyerAI.com
