🔍 Read the full analysis: Why Services Are 80% Of AI Business on ThorstenMeyerAI.com
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TL;DR
A November 9 essay on ThorstenMeyerAI.com argues that services grew as a share of U.S. jobs long before manufacturing employment peaked, reaching 86% of nonfarm payroll jobs in 2025. It uses Baumol’s cost disease to explain why many service costs rise even as factory-made goods get cheaper, and cites a customer-support study in which an AI assistant raised issues resolved per hour by 15% on average. How those gains will affect service-sector employment and costs remains uncertain.
A November 9, 2026, essay from ThorstenMeyerAI.com argues that services became the dominant part of the U.S. economy well before factory employment peaked, and examines whether AI can raise productivity in work that has historically been difficult to automate. The piece cites Bureau of Labor Statistics data showing service-providing industries accounted for 86% of U.S. nonfarm payroll jobs in 2025; a separate International Labour Organization estimate puts services at 79.6% of all U.S. workers.
The essay traces the service-sector shift across decades. Services made up 62% of U.S. payroll jobs outside farming in 1939, according to the article’s calculations from Bureau of Labor Statistics Current Employment Statistics. The share reached 72% in 1979, the year manufacturing employment peaked, and 86% in 2025. The payroll survey excludes farm workers and self-employed people, so those figures should not be treated as shares of all workers.
To explain why many services become more expensive, the article turns to Baumol’s cost disease, an idea developed by economists William Baumol and William Bowen in work on the performing arts. A string quartet still requires four musicians to play for roughly 45 minutes; unlike factory production, the performance cannot easily be shortened without changing the product. Meanwhile, productivity gains in industries such as manufacturing can raise wages across the economy, putting pressure on labor-intensive services to pay more even when their output per worker does not rise at the same rate.
The essay compares official, quality-adjusted U.S. price changes since 2000: television prices fell 98%, while hospital services rose 274%, college tuition rose 188%, and car repair rose 143%. These comparisons are presented as evidence of different price trajectories, not proof that Baumol’s theory alone caused each increase. 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. The source does not provide the study’s full title or methods in the supplied material.
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 Targets Labor-Heavy Services
The argument matters because services account for most U.S. jobs, yet many are built around human time and attention: care, teaching, repair, customer support and live performance. If AI increases output per worker in some of those areas, it could change how quickly providers handle work, how much labor they need, or how much they charge. The customer-support result offers one measured example of a productivity gain, but it does not establish that the same effect will occur across hospitals, schools, or other service industries.
The article’s central question is whether AI can make the historically slow-growing part of the economy more productive. That has consequences for workers and consumers, but a higher number of issues resolved per hour does not by itself show that prices will fall, service quality will hold steady, or jobs will disappear. Those outcomes depend on how employers use the tools and how savings or added capacity are distributed.
Prices also reflect more than productivity. The essay notes that U.S. health spending was 18.0% of the economy, compared with 12.4% in Germany, while pointing to institutional differences as a reason similar economic pressures can produce different bills. This comparison cautions against treating rising service costs as an automatic or complete consequence of the cost disease.
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From Quartet Costs to AI
Baumol and Bowen’s 1966 book, Performing Arts: The Economic Dilemma, examined financial pressures in theatre, opera, music and dance. Baumol developed the wider argument in a 1967 paper, proposing that economic activities differ in how readily they can raise output per hour. In some, such as manufacturing, machinery and process changes can reduce labor needed for a product. In others, labor is a larger part of the service itself, making productivity gains harder without changing what customers receive.
The source stresses that this is a difference of degree, not an absolute divide. Retail, for example, has changed through supermarkets and self-service; transport improvements can let a lecturer reach more people. The essay’s employment figures also challenge a simple story in which services grew only because factories declined: the service share was already 62% in 1939 and rose to 72% by 1979, before continuing upward.
The article is part of “Work After Work,” Episode 7, in a series about how the economy is built. Its historical examples frame AI as a new technology aimed at tasks in service work, rather than as evidence that the sector’s jobs or costs have already been transformed.
“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.”
— Thorsten Meyer, citing William Baumol and William Bowen’s discussion of the Schubert quartet
Productivity Gains, Employment Effects
The source cites a 15% average increase in issues resolved per hour among 5,172 customer-support agents, but the supplied text does not identify the study’s publication, date, design, or limits. The result therefore supports a specific claim about that study, not a general conclusion about AI’s effect on all service work.
It is also not yet clear whether productivity gains will reduce prices, increase service capacity, change job numbers, or do some combination. The employment shares and price changes show long-run patterns, but they do not establish that AI caused any of them. Nor does the supplied material break down how the 2025 service share varies by occupation or how much of the price increases reflects wages, financing, regulation, market structure, or other factors.
Evidence Needed on AI’s Reach
The next test is whether measured gains in customer support extend to other service occupations and persist outside a single study. Assessing that will require evidence on output, service quality, costs, staffing and worker pay over time—not just the number of tasks completed per hour.
Readers should also look for the underlying sources behind the article’s calculations and comparisons, including the BLS annual averages, the ILO employment estimate, price indexes, and the customer-support study. The essay frames AI’s effects on service-sector jobs as an open question; the material supplied does not announce a policy change, release date, or follow-up finding.
Key Questions
What is the main development in the article?
A November 9, 2026, essay examines why services dominate U.S. employment and whether AI can improve productivity in labor-intensive service work. It cites a 2025 estimate that services represented 86% of nonfarm payroll jobs.
Why does the article discuss a string quartet?
A quartet illustrates work where the service depends on human labor: four musicians playing for about 45 minutes require roughly three person-hours. The example helps explain Baumol’s cost disease, the idea that wages can rise in labor-intensive sectors even when their output per worker is difficult to increase.
Did AI increase productivity in the study cited?
The essay says a study of 5,172 customer-support agents found that an AI assistant raised issues resolved per hour by 15% on average. The supplied source does not give the study’s title, methods, or date, so the result should not be generalized to all service jobs.
Does the article show that AI will eliminate service jobs?
No. It raises job displacement and reassignment as open possibilities. The cited productivity result does not establish what will happen to total employment, pay, prices, or service quality.
Source: ThorstenMeyerAI.com
