U.S. Receptionist Employment and Wage Distribution

The receptionist labor market is large enough to shape the economics of telephone coverage, but a single “average salary” obscures most of the staffing story. The Bureau of Labor Statistics (BLS) estimated 1,000,530 wage-and-salary jobs for receptionists and information clerks, Standard Occupational Classification code 43-4171, across the United States in May 2023. The occupation’s national median was $16.94 per hour, while wages at the 10th and 90th percentiles were $12.54 and $23.82 per hour. Those are employer payroll jobs and hourly wage estimates, not prices for outsourced call handling or the earnings of self-employed workers.

This article uses the detailed May 2023 Occupational Employment and Wage Statistics (OEWS) occupation profile as its fixed wage benchmark. The Occupational Outlook Handbook and BLS Employment Projections provide the forward-looking context. Census methodology and classification sources are used to explain why household-based estimates should not be treated as interchangeable with OEWS employer estimates.

National employment is substantial, but it is not a count of phone-only agents

The May 2023 OEWS estimate of 1,000,530 jobs covers the United States and represents employment in the occupation, not one million individual establishments or full-time equivalents. The BLS definition includes people who answer inquiries and provide information to the public, but the occupation also encompasses greeting visitors, scheduling appointments and performing related clerical duties. A dental front-desk employee who alternates between calls, patient arrival and appointment work can therefore be in the same occupation as a receptionist whose day is dominated by telephone traffic.

That scope matters for answering-service capacity analysis. The employment total establishes the scale of the labor pool associated with first-contact and information-routing work. It does not establish the number of people available for remote answering, the number of simultaneous calls they can handle or the portion of paid time spent on the telephone. No conversion from receptionist jobs to call capacity is defensible without establishment-level data on schedules, occupancy, call duration and non-call duties.

OEWS is designed to produce employment and wage estimates by occupation, industry and geography. Its national tables, state tables and area tables are separate views of the same employer-survey program. For staffing, this means the national figure is the right U.S. benchmark, while recruiting assumptions tied to one city or state should use the corresponding local table rather than a national average.

The wage distribution is wider than the median suggests

The national May 2023 OEWS wage distribution for U.S. receptionists and information clerks was:

BLS also reported a $18.01 mean hourly wage and $37,450 mean annual wage for this U.S. occupational cohort in May 2023. OEWS annual wages are standardized from hourly estimates on a full-time, year-round basis of 2,080 hours; they are not a finding that every receptionist worked 2,080 paid hours. The percentile figures describe the distribution of jobs, not a career ladder in which one worker necessarily progresses from the 10th to the 90th percentile.

The operational implication is more precise than “labor costs vary.” A staffing model anchored only to the $16.94 national median ignores both tails of the observed employer wage distribution. Coverage requiring scarce-language ability, specialized intake, difficult hours or work in a high-wage local market may compete with jobs farther up that distribution. Conversely, the 10th percentile is not a safe universal hiring rate: it marks a lower point in the national distribution and says nothing about local wage law, experience requirements, benefits or schedule desirability.

The mean exceeds the median, indicating that higher-paid jobs pull the average upward. For cost comparisons, “average” must therefore be labeled. The May 2023 U.S. mean was $18.01 per hour; the median was $16.94 per hour. Substituting one for the other can create a material difference before payroll taxes, benefits, supervision, recruiting, absence coverage or technology are considered.

Industry concentration changes the meaning of receptionist supply

The Outlook Handbook reports that healthcare and social assistance is the largest employer of receptionists. This concentration is consistent with the occupation’s mix of appointment scheduling, visitor reception, record handling and telephone inquiry work. It also means the national labor pool is not uniformly transferable across use cases. Experience at a medical practice may include protected information, clinical escalation boundaries and appointment terminology; experience in personal care, real estate or professional services creates a different context.

For answering-service staffing, occupational headcount is therefore a broad supply indicator rather than a count of immediately qualified agents. Industry knowledge can affect training time and the share of contacts that require escalation. The BLS OEWS tables permit industry-by-occupation analysis, but they do not measure script adherence, call quality, bilingual proficiency, security clearance or familiarity with a client’s software.

Geography adds a second layer. OEWS publishes state, metropolitan and nonmetropolitan estimates because wage levels and occupational concentration differ across labor markets. A distributed answering operation can recruit across more than one market, but national remote access does not erase state wage rules, time-zone coverage, broadband constraints or the local alternatives available to workers. The evidence supports geographically differentiated labor assumptions; it does not identify a universally lowest-cost location.

Limited net growth can coexist with large annual hiring demand

Employment projections distinguish changes in the total number of jobs from openings created when workers permanently leave an occupation. The current Outlook Handbook projects 0 percent employment change from 2024 to 2034—classified as little or no change—while still showing roughly 128,500 openings per year, on average, across the United States during that decade. BLS attributes most openings to replacement needs rather than net occupational expansion.

That distinction is central to staffing interpretation. A flat or declining job count does not imply a frozen recruiting market. Employers still hire because people retire, change occupations or otherwise exit. Answering operations compete in that replacement market even when technology reduces some routine receptionist tasks. The BLS National Employment Matrix occupational documentation should be used when comparing projection periods because an openings figure, an employment-change figure and a current employment estimate measure different things and are not additive substitutes.

Technology also affects tasks unevenly. Automated scheduling, kiosks and messaging can reduce routine contacts, but the occupation still includes situations requiring interpretation, reassurance and routing. The projection is evidence about national occupational employment, not a forecast of inbound call volume, automation accuracy or the optimal human-to-automation mix for any one organization.

What the evidence means for answering-service staffing

Three measured features shape labor planning. First, the occupation had about one million U.S. payroll jobs in May 2023, so receptionist work is a broad labor market rather than a niche role. Second, the national wage distribution spans from $12.54 at the 10th percentile to $23.82 at the 90th percentile per hour, before employer on-costs. Third, projected annual openings remain large even without strong net job growth, indicating continuing replacement competition.

Together, these findings favor staffing assumptions that separate base wage, paid coverage and productive call time. OEWS can benchmark the first item. It cannot supply the second or third. A paid receptionist hour may include breaks, training, documentation, visitor assistance, scheduling and idle time needed to preserve responsiveness. Shared answering capacity may pool uneven call arrivals across clients, while dedicated staffing may preserve deeper account context; BLS data do not quantify either effect.

The distribution also argues against treating a national median as a vendor-rate comparator. An employer wage excludes many components of fully loaded labor, while a contracted rate may include management, technology and coverage redundancy. The two are different units. The labor data are most useful for understanding recruitment pressure and the wage portion of an employment model, not for declaring one delivery model cheaper.

Limitations

OEWS is an establishment survey of wage-and-salary employment and excludes self-employed workers. Its estimates are subject to sampling and nonsampling error; BLS explains reliability, collection and estimation in its survey methods and frequently asked questions. National percentiles cannot reveal an individual worker’s pay, and annualized wages do not describe actual annual hours for part-time employees.

The May 2023 wage table is a historical snapshot and is not inflation-adjusted to August 2026. The outlook uses a different reference period and a projection model, so its employment level should not be merged with the May 2023 OEWS estimate as if both described the same date. Occupational classifications also impose boundaries that real jobs may cross.

Finally, household surveys answer different questions. The Census Bureau’s American Community Survey methodology, occupation code lists and crosswalks, and Current Population Survey methodology document different universes, collection designs and coding systems. ACS or CPS estimates can add demographic or worker-level context, but they should not be expected to reproduce OEWS payroll-job counts. None of these sources measures answering-service response time, abandonment, concurrent demand, schedule adherence or service quality. Those operational outcomes require separate, directly observed data.