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TL;DR
A November 9, 2026, article from ThorstenMeyerAI.com reports that services made up 79.6% of U.S. employment in 2025, using International Labour Organization estimates. It connects that shift 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; how those gains will affect service-sector jobs remains uncertain.
Services accounted for 79.6% of U.S. employment in 2025, according to International Labour Organization estimates cited in a November 9 analysis by ThorstenMeyerAI.com. The article links the long-term growth of service work to Baumol’s cost disease and examines whether AI productivity gains will change jobs in industries where human attention is part of the service.
The article distinguishes the ILO estimate, which counts all workers, from a separate calculation using U.S. Bureau of Labor Statistics payroll data. That calculation puts services at 86% of nonfarm payroll jobs in 2025. The payroll series excludes farm workers and self-employed people. It shows services already represented about 62% of nonfarm payroll jobs in 1939, rising to 67% in 1967 and 72% in 1979. The figures indicate that services expanded before U.S. manufacturing employment peaked in June 1979, as well as after it.
The analysis uses a string quartet to explain why some work is hard to make more productive without changing the service itself. Four musicians performing a 45-minute piece contribute about three hours of labor, a requirement the article says has not changed since Schubert’s time. Economist William Baumol developed this idea into a broader account of uneven productivity growth: manufacturing can often produce more with fewer labor hours, while teaching, medical care and live performance rely on time and attention from people.
To illustrate differing price trends, the article reports that U.S. television prices, adjusted for quality, fell 98% between 2000 and 2025, while hospital services rose 274%, college tuition 188% and car repair 143%. These are comparisons reported in the source, not proof that productivity alone caused each price change. The article also cites a study of 5,172 customer-support agents in which an AI assistant increased issues resolved per hour by 15% on average.
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 figures matter because services now account for most U.S. employment, but many service tasks do not become faster simply because other parts of the economy do. Under Baumol’s account, wages in labor-intensive occupations may rise alongside wages in more productive industries, even when output per worker changes little. That can put upward pressure on the costs of services such as care, education and performance.
AI could alter some of those constraints by helping workers complete certain tasks more quickly. The cited customer-support study offers evidence of a productivity gain in one setting, but it does not establish that all service jobs can be automated or that higher output will reduce prices. The gains could instead change staffing, workload, service quality or the mix of tasks workers perform. The article frames the central question as whether AI will shrink service-sector employment or redirect workers toward tasks that remain difficult to automate.
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Services Grew Before Factory Decline
The article challenges the idea that services expanded only because manufacturing jobs disappeared. BLS payroll data cited in the analysis show a rising service share from 1939 onward, well before manufacturing employment reached nearly 20 million in June 1979. That history suggests a broader structural shift, rather than a simple replacement of factory work by services after the industrial peak.
Baumol and William Bowen’s 1966 book, Performing Arts: The Economic Dilemma, examined the finances of theatre, opera, music and dance. Baumol’s 1967 paper, “Macroeconomics of Unbalanced Growth: The Anatomy of Urban Crisis,” applied the productivity distinction to the economy. The source also cautions against treating service prices as the result of one factor: U.S. health spending, for example, is reported at 18.0% of the economy, compared with 12.4% in Germany. Different national spending levels show that institutions and policy can affect costs alongside the underlying difficulty of raising productivity.
How AI Gains Affect Jobs
The source does not identify the customer-support study by title, publication venue or date, so readers cannot determine from the article alone how the research was designed or whether its results have been independently replicated. Its 15% figure is an average for the agents studied, not a forecast for every service occupation or a measure of jobs eliminated.
It is also unclear whether AI-enabled productivity will translate into lower prices, higher wages, improved service, reduced staffing or some combination. The employment shares describe the composition of the workforce; they do not show what caused individual price increases. The article provides no projection for how the U.S. services share or service-sector employment will change as AI adoption spreads.
Evidence Needed on AI’s Effects
The next steps for understanding the story are further evidence on how AI tools perform beyond the customer-support setting and how organizations use the time they save. Relevant measures would include changes in staffing, wages, service quality, prices and the range of work assigned to employees, tracked over time rather than inferred from a single productivity result.
The source presents the future of service employment as an open question and does not name a scheduled study, policy decision or employment release that will resolve it. For now, the reported labor shares establish how large the service economy is, while the cited AI finding offers a limited example of productivity improvement—not evidence that service-sector jobs are about to disappear.
Key Questions
What does the 80% figure refer to?
It refers to the ILO estimate cited in the article: 79.6% of U.S. workers were in services in 2025. A separate BLS-based calculation gives services 86% of nonfarm payroll jobs, a different measure that excludes farm workers and the self-employed.
What is Baumol’s cost disease?
It describes how costs can rise in labor-intensive work when wages increase across the economy but productivity in some services is difficult to raise. Teaching, medical care and live performance are examples discussed in the article.
Does the customer-support study show that AI will eliminate jobs?
No. The source reports that an AI assistant raised issues resolved per hour by 15% on average among 5,172 agents. That result measures productivity in the studied setting; it does not establish how many jobs may be created or lost.
Did services grow only after U.S. factories declined?
No. The BLS payroll figures cited in the article put services at about 62% of nonfarm payroll jobs in 1939, rising to 72% by 1979, when manufacturing employment reached its reported peak. The service share continued to rise afterward.
Why do service prices vary between countries?
The article points to U.S. health spending of 18.0% of the economy, compared with 12.4% in Germany, as evidence that costs also reflect national institutions and policy. It does not claim that Baumol’s theory alone explains the difference.
Source: ThorstenMeyerAI.com
