🔍 Read the full analysis: How AI Redefined Work As Services on ThorstenMeyerAI.com
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TL;DR
A November 9 report examines how AI could affect service work, where productivity has historically been harder to raise than in manufacturing. 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 does not establish whether such gains will reduce service costs or employment.
A November 9 report on the economics of service work says AI is beginning to raise measured productivity in areas where output has traditionally been difficult to increase, citing a study in which an AI assistant helped 5,172 customer support agents resolve 15% more issues per hour on average. The finding matters because service industries now account for most US jobs, but it does not show whether AI will lower prices, reduce staffing or change the quality of service.
The report uses Baumol’s cost disease to explain why services can become more expensive even when productivity in other parts of the economy rises. In manufacturing, machinery and new production methods can let workers produce more in the same amount of time. In some services, however, the work itself requires human attention: a quartet still needs musicians to perform the piece, while teaching and medical care can depend on personal interaction.
US Bureau of Labor Statistics payroll data cited in the report show that service-providing industries accounted for 62% of nonfarm payroll jobs in 1939, 72% in 1979 and 86% in 2025. The figures are annual averages and exclude farm workers and self-employed people. Separately, International Labour Organization estimates put services at 79.6% of all US employment in 2025. The measures have different coverage, so they should not be treated as interchangeable.
The report also compares selected US prices from 2000 to 2025: the official quality-adjusted price of televisions fell 98%, while hospital services rose 274%, college tuition 188% and car repair 143%. These are changes over that stated period, not a complete account of household costs or the causes behind them. The report notes that haircuts and car repairs also rose, suggesting that health insurance and student loans alone do not explain rising service prices.
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 Hard-to-Scale Services
The 15% result offers evidence that AI can help workers handle more service requests per hour in at least one studied setting. If similar gains are reproduced across other tasks, businesses could serve more customers with the same staff, reduce response times, or shift workers toward cases that need more judgment. Those are possible outcomes, not results established by the reported average.
The larger economic question is whether better productivity will ease the cost pressures associated with labor-intensive services. A productivity gain does not automatically lead to lower prices: firms may keep prices steady, raise wages, invest in the technology or change staffing. The source provides no evidence that the customer-support finding has already lowered prices or caused job losses.
For workers, the distinction is consequential. AI may automate parts of a job without eliminating the job itself, and the effect can differ by occupation, employer and task. The report frames this as an open question: whether technology reduces the amount of labor required or moves workers into new service work that remains difficult to scale.
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Services Grew Before Factory Decline
The report challenges a simple account in which service employment rose only because factory jobs disappeared. Its BLS series begins in 1939, decades before US manufacturing employment reached nearly 20 million in June 1979, a peak discussed in an earlier episode of the source publication. The service share had already reached 72% of nonfarm payroll jobs by 1979 and continued increasing afterward.
The economic framework comes from William Baumol and William Bowen’s 1966 book on the performing arts and Baumol’s 1967 paper on unbalanced economic growth. Their example contrasts a factory process that can be redesigned to use less labor with a live performance that still requires musicians to play. Baumol described the distinction as one of degree: technology can improve productivity in some service activities, but the scope for doing so varies.
The wage mechanism is central to the theory. If productivity raises pay in sectors where output per worker grows quickly, employers in slower-growing fields may also need to raise wages to retain workers. When those services cannot produce proportionally more output, their labor costs per unit can rise. The theory helps explain a pattern; it does not by itself establish why any individual price increased.
““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 and William Bowen, quoted in the report from their performing-arts research
What the AI Study Cannot Show
The source summary does not provide the customer-support study’s publication details, research design, date, participating organizations or the range of results among agents. It reports a 15% average increase in issues resolved per hour, but does not say whether the result was peer-reviewed or how the researchers measured resolution quality. Readers cannot infer from the summary whether the gain applies to other employers or service jobs.
It is also unclear whether higher throughput improved customer outcomes, changed workers’ pay or hours, reduced headcount, or lowered prices. The report does not present evidence on those outcomes. Nor does it establish that AI can meaningfully speed up work such as live music, classroom teaching or complex medical care, where human interaction may be part of the service’s value.
The price comparisons require care, too. The supplied material gives changes for selected categories between 2000 and 2025, but does not provide the underlying index tables or a detailed explanation of how each category was measured. The figures identify a contrast; on their own, they do not prove Baumol’s theory or assign responsibility for price increases.
Evidence Needed on Jobs and Costs
The next step is to see whether the customer-support result holds in other workplaces and over longer periods. More detail on the study’s methods, quality measures and worker outcomes would help determine whether the reported increase reflects faster handling, better resolution, or both. Comparable results across industries would show how broadly AI is changing service productivity.
For customers and workers, the outcomes to watch are service prices, wait times, quality, staffing and wages. The report does not announce a future policy decision or a scheduled research milestone. Its central question remains unresolved: whether AI will make labor-intensive services less costly, change who performs them, or mainly increase the amount of work businesses can handle.
Key Questions
What is Baumol’s cost disease?
Baumol’s cost disease is an economic explanation for why costs can rise in sectors where productivity is difficult to increase. If wages rise across the economy while output per worker grows slowly in some services, the labor cost of providing those services can increase.
What did the customer-support study find?
The report says a study involving 5,172 customer support agents found that an AI assistant raised issues resolved per hour by 15% on average. The supplied summary does not give enough methodological detail to assess the result’s scope or effect on service quality.
Does the reported productivity gain mean AI will eliminate support jobs?
No. The reported average measures issues resolved per hour, not job losses. The source does not establish whether employers reduced staffing, changed working hours or reassigned workers after using the assistant.
Did service employment grow only after factory jobs declined?
No, according to the BLS payroll figures cited in the report. Services accounted for 62% of nonfarm payroll jobs in 1939, before the 1979 manufacturing-employment peak discussed in the source. The share reached 72% in 1979 and 86% in 2025.
Source: ThorstenMeyerAI.com
