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TL;DR
The source essay argues that services made up about four in five U.S. workers in 2025 and that the shift began well before manufacturing employment peaked in 1979. It connects rising service costs 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. Whether those gains reduce costs or change service employment remains unanswered.
A November 9 essay from ThorstenMeyerAI.com argues that services accounted for about four in five U.S. workers in 2025 and examines whether artificial intelligence can lift productivity in work where human attention is central. The piece connects the rise of services to economist William Baumol’s account of why some labor-intensive activities become more expensive as productivity increases elsewhere.
The essay gives two measures of the service economy. Its calculation from U.S. Bureau of Labor Statistics payroll data puts service-providing industries at 86% of nonfarm payroll jobs in 2025. The International Labour Organization’s estimate, which counts all workers, places the U.S. services share at 79.6% in 2025. Those figures use different populations and should not be treated as interchangeable.
The payroll-job share was already 62% in 1939, according to the essay’s calculation, then rose to 67% in 1967 and 72% in 1979. That timeline challenges the idea that services grew only after U.S. factory employment began to fall: the service share had been increasing well before manufacturing reached its employment peak in June 1979.
To explain why service work can resist productivity gains, the essay revisits Baumol and William Bowen’s research on the performing arts. Their example is a live 45-minute Schubert quartet, requiring four musicians for about three hours of labor. The source says the same basic labor requirement applies today as it did two centuries ago, unlike factory production, where machinery and process changes can reduce labor per unit.
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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Why Service Costs Keep Rising
The argument matters because it offers one explanation for the pressure on prices in sectors such as health care, education, repairs and personal services. In Baumol’s framework, wages in less productive activities still rise as workers can seek higher pay in more productive parts of the economy. If the labor required for a service does not fall at the same pace, its cost can rise relative to goods made with increasingly efficient production.
The essay illustrates the contrast with U.S. price changes since 2000: it reports that the quality-adjusted price of a television fell 98%, while hospital services rose 274%, college tuition 188% and car repair 143%. These are figures as presented in the source; the essay does not provide the underlying data series in the supplied material. It also notes that haircuts and repairs became more expensive without the role of health insurers or student loans, so those institutions alone cannot explain the broader pattern.
AI could alter the calculation if it helps workers resolve more cases, prepare information or handle routine tasks without reducing service quality. The essay cites a study of 5,172 customer-support agents in which an AI assistant raised issues resolved per hour by an average of 15%. That is evidence of a measured productivity gain in one setting, not proof that AI will lower prices across services or eliminate the need for workers.
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From Quartet Economics to AI
Baumol and Bowen examined the financial pressures facing theater, opera, music and dance in their 1966 book, Performing Arts: The Economic Dilemma. In 1967, Baumol developed the productivity distinction in an American Economic Review paper. Some activities are technologically progressive: machines, investment and economies of scale can increase output per worker. In others, including teaching, medical attention and live performance, labor itself is a substantial part of what the customer receives.
The source emphasizes that this is a difference of degree, not an absolute division. Retail has changed through supermarkets and self-service, and technology can make some professional work more productive. But the quartet remains a useful illustration of tasks in which simply speeding up the labor could undermine the service being offered.
The employment figures also depend on definitions. The BLS payroll series described in the essay excludes farm workers and self-employed people, while the ILO estimate covers all workers. The source says services include activities ranging from shops and transport to hospitals, schools, offices and government, rather than a single uniform kind of job.
What AI Productivity Gains Mean
The source does not identify the full study details behind the 15% average productivity gain, including its date, setting, duration or how researchers measured quality. It also does not establish whether the result applies to other service jobs, such as nursing, teaching or repairs.
It remains unclear whether AI-driven gains will reduce prices, raise service quality, increase output, or lead employers to change staffing. The essay poses the possibility that workers could move into tasks that remain difficult to automate, but does not provide employment forecasts. Its price comparisons also do not, by themselves, show how much of each increase came from productivity, wages, regulation, financing or other factors.
The Test for AI in Services
The next evidence to watch is whether productivity results from customer support can be reproduced in other workplaces and sustained over time. Useful assessments would track not only cases handled per hour, but also accuracy, customer satisfaction, worker workload and the cost of delivering the service.
For the broader argument, future employment and price data will show whether the service share continues to rise and whether AI changes that path. The source essay presents AI as a potential tool for the sector where labor productivity has historically been harder to raise; it does not establish yet that the technology will reverse service-cost growth or shrink the workforce.
Key Questions
What does the “80%” refer to?
The source cites an International Labour Organization estimate that services accounted for 79.6% of all U.S. workers in 2025. A separate BLS-based calculation puts services at 86% of nonfarm payroll jobs; that measure excludes farm workers and self-employed people.
What is Baumol’s cost disease?
It is an economic explanation for why labor-intensive services can become more expensive relative to goods. If workers’ wages rise across the economy while productivity in some services grows slowly, the labor cost of providing those services can increase.
Does the cited AI study show that AI will replace service workers?
No. The essay reports that an AI assistant increased issues resolved per hour by an average of 15% among 5,172 customer-support agents. That result does not establish that workers will be replaced or that the same effect will occur in other jobs.
Why does the essay compare a quartet with factory production?
A quartet requires musicians to perform for the length of the piece, so reducing labor time could change the service itself. Factory methods can often produce more goods with less labor per unit, making the contrast an illustration of different productivity limits.
Source: ThorstenMeyerAI.com
