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TL;DR
A November 9 report links AI’s arrival in service work to Baumol’s cost disease, the idea that jobs with limited productivity growth become more expensive as wages rise across the economy. It cites a study of 5,172 customer-support agents in which an AI assistant increased issues resolved per hour by 15% on average; how that gain affects employment remains unknown.
A November 9 report on AI and service work points to a study of 5,172 customer-support agents in which an AI assistant raised the number of issues resolved per hour by 15% on average. The finding offers evidence that AI can improve productivity in at least one service setting, but it does not show whether companies will need fewer workers or whether employment will shift to other tasks.
The report places the study within Baumol’s cost disease, an economic argument about work where productivity is difficult to increase because human time is central to the service. A live string quartet still requires four musicians to play a piece, while manufacturing has repeatedly found ways to produce goods with less labor. The report argues that AI is now being aimed at service tasks where such productivity gains have historically been harder to achieve.
The cited customer-support result measures issues resolved per hour, not job losses, wage changes or total company costs. The report does not identify the study’s researchers, publication, date, workplace setting or research design in the supplied material. Its figure should therefore be read as a reported study result, not as proof that the same gain will occur across the service economy.
The article also describes the long growth of US services. Its calculation from Bureau of Labor Statistics payroll data puts service-providing industries at 62% of nonfarm payroll jobs in 1939, 72% in 1979 and 86% in 2025. The payroll series excludes farm workers and self-employed people. Separately, International Labour Organization estimates put services at 79.6% of all US workers in 2025, a different measure with a broader worker base.
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 reported productivity gain matters because services account for a large share of work, and many services depend on time and attention from people. If AI lets workers resolve more customer issues per hour, employers may be able to handle more demand with existing staff, shorten waiting times, or change how tasks are divided. The study result alone does not establish which outcome will follow.
That distinction is important for workers and customers. A productivity increase can support growth in output without reducing headcount; it can also lead employers to redesign jobs or limit hiring. The report raises the question of whether AI will reduce pressure from rising service costs or move workers toward other roles, but supplies no employment data to settle it.
The same framework helps explain why prices can rise even when there is no clear equivalent of a factory productivity breakthrough. The report gives official, quality-adjusted US price comparisons since 2000: televisions fell 98%, while hospital services rose 274%, college tuition 188% and car repair 143%. These figures cover different goods and services and do not, on their own, explain every cause of price changes.
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How Baumol Explained Service Costs
Economists William Baumol and William Bowen examined the finances of performing arts in their 1966 book, Performing Arts: The Economic Dilemma. The example that became widely cited was a 45-minute Schubert quartet: three hours of musicians’ labor, with little scope to reduce the time without changing the performance. Baumol developed the wider argument in a 1967 paper on economic growth and urban services.
In Baumol’s model, some activities gain productivity through technology and scale, while others depend more directly on labor. If wages rise in the more productive parts of the economy, employers in the slower-growing activities may also have to raise pay to retain workers. Their costs can rise even when the time needed to provide the service has not fallen. Baumol described the categories as a matter of degree, not a strict division between jobs.
The report’s US employment figures also complicate a simple story in which services expanded only after factories declined. Services made up a majority of nonfarm payroll employment as far back as 1939, according to the article’s BLS-based calculation, and their share rose both before and after manufacturing employment peaked in 1979.
What the Productivity Figure Cannot Show
The supplied report gives the customer-support study’s sample size and average productivity result, but not its publication details, methods, duration or setting. It is not clear how the researchers defined an issue being resolved, whether results varied among agents, or how the AI assistant affected accuracy and customer satisfaction.
Nor does the 15% figure establish an effect on employment. The source provides no information about staffing levels, hiring, pay, hours or the number of jobs affected. It also does not show whether the result can be replicated in other service industries, where tasks and measures of quality differ.
The price comparisons and employment shares are presented as supporting context, not as evidence that AI has already lowered service costs or changed the size of the service workforce. Those outcomes remain unconfirmed.
Evidence Needed on Jobs and Costs
The next useful evidence would include the full customer-support study, with its methods, workplace conditions and measures of quality, alongside follow-up data on whether the productivity result lasts. Reporting on staffing, hours, wages and hiring would help show how employers use any time saved.
For the wider service economy, the key question is whether AI raises output while preserving service quality, and whether those gains reduce costs or change demand for workers. The source article frames that as an open question; it provides no timeline or forecast for when broader effects might become visible.
Key Questions
What does “80% of roles” refer to?
The source uses an International Labour Organization estimate that 79.6% of US workers were in services in 2025. That is a share of workers, not a claim that AI can perform 80% of jobs or tasks.
What productivity gain did the customer-support study report?
The report says an AI assistant increased the number of issues resolved per hour by 15% on average among 5,172 customer-support agents. The supplied material does not give the study’s methods or publication details.
Does the study show that AI is eliminating service jobs?
No. The reported result concerns issues resolved per hour. The source provides no figures on job losses, staffing, hiring, wages or hours worked.
What is Baumol’s cost disease?
It describes how costs can rise in activities where productivity is difficult to increase, such as live performance or some forms of care. If wages rise elsewhere in the economy, these sectors may also need to raise pay even when they cannot reduce the labor time needed to provide their service.
Source: ThorstenMeyerAI.com
