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TL;DR
A Nov. 9, 2026, report argues that the U.S. shift toward service work began decades before manufacturing employment peaked, and examines how Baumol’s cost disease helps explain rising costs in labor-intensive services. It cites a study of 5,172 customer-support agents in which an AI assistant increased issues resolved per hour by 15% on average, but says the broader employment effects remain uncertain.
A report published November 9, 2026, examines how AI may affect service work, an increasingly large part of the U.S. economy, through the lens of economist William Baumol’s theory of rising costs in labor-intensive industries. The report cites a study of 5,172 customer-support agents in which an AI assistant increased the number of issues resolved per hour by 15% on average, while leaving open whether such productivity gains will reduce service jobs or change the work people do.
The report says services grew as a share of U.S. employment well before manufacturing jobs reached their peak in June 1979. Bureau of Labor Statistics payroll data, as calculated by the report, show service-providing industries accounted for 62% of nonfarm payroll jobs in 1939, 72% in 1979 and 86% in 2025. The figures exclude farm workers and self-employed people. Separately, International Labour Organization estimates put services at 79.6% of all U.S. workers in 2025.
To explain why service costs can rise even as other industries become more productive, the report revisits Baumol’s work with economist William Bowen on performing arts. Their example is a string quartet: a 45-minute performance still requires four musicians, or about three hours of labor. In a 1967 paper, Baumol described a contrast between industries where technology can repeatedly reduce labor per unit of output and activities where human labor is itself a large part of the service.
The report compares U.S. prices from 2000 to 2025: the quality-adjusted price of a television fell 98%, while hospital services rose 274%, college tuition 188% and car repair 143%. It also says haircuts more than doubled in price. These are figures presented in the source report; they cover different categories and do not by themselves establish a single cause for each price change.
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 the service sector now represents most U.S. employment, while many services depend on time and attention that are difficult to scale in the way factory production can. Baumol’s theory offers one explanation for why wages and costs may rise in these fields even when their output per worker improves more slowly than in technology-intensive industries.
The customer-support result suggests AI can help workers handle more cases per hour, but it does not establish what happens to staffing, wages, service quality or total costs. The report frames this as a central question: whether AI reduces demand for workers or shifts them toward tasks that remain difficult to automate. The study’s 15% average productivity result is a finding for a specific group and setting, not evidence that all service jobs will see the same effect.
That distinction is relevant to workers, employers and customers. If AI improves throughput without reducing the human attention customers need, it could change how services are delivered. If organizations use productivity gains to cut staff, the effects on jobs and service quality could be different. The source material does not resolve which outcome will predominate.
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From Orchestras to Service Work
Baumol and Bowen studied the economics of performing arts in their 1966 book, Performing Arts: The Economic Dilemma. The report highlights their observation that a live quartet cannot readily reduce the musicians’ labor while performing the same piece. Baumol developed a broader account in his 1967 paper, Macroeconomics of Unbalanced Growth: The Anatomy of Urban Crisis.
The underlying idea is that productivity can rise much faster in some industries than in others. When wages rise across the economy, labor-intensive services may face higher costs even if the time required to deliver them changes little. The report stresses that this is a difference of degree, not a strict division: technology can also improve productivity in services, and the nature and quality of work matter.
The employment figures also complicate a common account of the U.S. economy: that services expanded only after factories declined. In the report’s BLS series, services already made up a majority of nonfarm payroll jobs in 1939, and their share continued to grow both before and after manufacturing employment peaked.
““Human ingenuity has devised ways to reduce the labor necessary to produce an automobile, but no one has yet succeeded in decreasing the human effort expended at a live performance of a 45-minute Schubert quartet much below a total of three man-hours.””
— William Baumol, quoted in the report from his 1967 paper
AI’s Effect on Service Jobs
The source material does not identify the customer-support study by name, publication venue, date, or research team, and it provides no detail about the study design or comparison conditions. The reported 15% average increase therefore cannot, from the supplied information alone, be independently assessed or generalized to other workplaces.
It is also unclear whether AI-driven productivity gains will reduce the number of service workers, increase the volume of work handled, improve service quality, or produce a mix of those outcomes. The report does not provide evidence that AI has already lowered prices across the service economy. Nor do its long-term price comparisons isolate the effect of Baumol’s cost pressures from other possible influences, including financing systems, regulation and changes in service quality.
Evidence Needed on AI’s Reach
The next evidence to watch is whether the customer-support result is replicated in other studies and types of service work, and whether measured productivity changes persist outside controlled or limited settings. Longer-term data on staffing, wages, resolution quality and customer experience would help show what the gains mean in practice.
For now, the report presents AI as a new tool aimed at work that has historically been harder to automate than factory production, not as proof that service-sector employment is about to shrink. Further research and workplace data will be needed to establish how widely the technology is being adopted and who benefits from the resulting productivity gains.
Key Questions
What is Baumol’s cost disease?
It is an economic theory about why costs can rise in labor-intensive services when productivity improves more slowly than in other industries. If wages rise across the economy, service employers may also need to pay more even when the labor time needed for a performance, lesson or personal service changes little.
How large is the U.S. service sector?
The report says service-providing industries accounted for 86% of U.S. nonfarm payroll jobs in 2025, based on its calculation from BLS data. A separate ILO estimate cited in the report puts services at 79.6% of all U.S. workers that year.
What did the customer-support AI study find?
In a study of 5,172 customer-support agents, an AI assistant raised the number of issues resolved per hour by 15% on average, according to the report. The supplied source does not give the study’s publication details or enough methods to establish how broadly the result applies.
Does the study show AI will eliminate service jobs?
No. The reported productivity result does not establish whether employers will reduce staffing, handle more work with the same number of employees, or change job duties. The wider employment effects remain uncertain.
Source: ThorstenMeyerAI.com
