Waiters and waitresses
Also called Server, Waiter, Waitress, Restaurant server, Food server
In brief
In May 2025, BLS counted 2,270,910 US waiters and waitresses, with median pay of $35,230 a year. Of the BLS counts since 2021, the highest was 2,302,690, in May 2024, close to the May 2025 count. The earliest figure here is an estimate of 200,000 from 1900, not measured the same way as today's count. The last full technology era for waiters and waitresses: Toast handheld POS + delivery platform integration, 2015 to 2020.
What the sources say
Official outlook
BLS projects employment to grow 2% from 2025 to 2035.
AI exposure studies
- 22.4% of this job's tasks are exposed to large language models. Not a forecast of job losses. Eloundou and others, 2023
- 0.94 estimated probability that the whole occupation could be computerised, over an unspecified number of years. Not a forecast of job losses. Frey and Osborne, 2013
Since the 2013 prediction
In 2013, Frey and Osborne put this job's probability of computerisation at 0.94. BLS counted 2,403,960 of these jobs in May 2013 and 2,270,910 in May 2025. The count moved sharply in one step, May 2020 to May 2021, when BLS changed how it estimates these counts, so no change is derived here.
Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend. In May 2021 BLS changed how it estimates these counts (a model-based method using three years of survey data) and moved fully to the 2018 occupation codes, so part of a change across 2021 can come from the method rather than the work.
Last updated .
Cite this page
Future History. (2026, October 11). Waiters and waitresses: jobs and pay since 1900 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/35-3031
Future History. "Waiters and waitresses: jobs and pay since 1900." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/35-3031.
@misc{futurehistory_35_3031, author = {{Future History}}, title = {Waiters and waitresses: jobs and pay since 1900}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/35-3031}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }
The access date is today's date on your device.
≈ $34,327 in 2024 prices (derived by us, CPI-adjusted)
Delmonico's opens its landmark restaurant at 2 South William Street in lower Manhattan: America's first à la carte restaurant. The brothers Giovanni and Pietro Delmonico, joined by their nephew Lorenzo, introduce cloth-covered tables, a bilingual French-English printed menu, private dining rooms, and a professional service staff trained to attend guests at individual tables rather than a common board. The waiter role as a distinct American profession (separate from tavern service, different from domestic help) is born here. Dishes invented at Delmonico's (Lobster Newberg, Baked Alaska, Eggs Benedict) enter the American culinary canon; so does the idea that the person who serves them is performing a skilled occupation.
Fred Harvey fires his entire male waitstaff at the Raton, New Mexico station following a drunken brawl and replaces them with women: the Harvey Girls. From 1883 onward, the Fred Harvey Company hires only women as restaurant waitresses at its chain of Atchison, Topeka and Santa Fe Railroad dining rooms. Selection criteria: single, aged 18-30, educated, "good character," willing to sign a one-year no-marriage contract. Roughly 100,000 Harvey Girls worked in the system between 1883 and the 1950s. The move was commercially motivated but had significant cultural consequences: it opened professional food-service employment to women at scale for the first time, established the standardized-service protocol system that underlies all chain-restaurant training, and created a model of the waitress as a professional rather than a domestic servant.
Horn & Hardart opens the first American Automat at 818 Chestnut Street in Philadelphia: a coin-operated, self-service restaurant with no waiters. Food is visible behind glass compartment windows; customers insert nickels, lift a window, and take their own food. By the 1940s, Horn & Hardart is the world's largest restaurant chain with over 80 New York City locations. The Automat represents the first major technology displacement prediction for restaurant servers, and the first time the prediction fails. Waiter and waitress employment grows substantially during the same decades that Horn & Hardart expands, because the Automat serves a different occasion (quick urban lunch) rather than competing for the full-service dining occasion.
The 1966 amendments to the Fair Labor Standards Act extend federal minimum-wage coverage to restaurant and hotel workers for the first time: a workforce of millions that had previously operated outside federal wage-floor protection. The same amendments create the "tip credit" mechanism: employers can pay tipped workers below the standard minimum wage if tips bring total compensation up to minimum wage. This is the legal foundation of the American tipping economy. The original tip credit was a 50-50 split (employers paid half the minimum wage, tips covered the rest). A 1996 FLSA amendment then severed the tipped cash wage from the regular minimum wage, freezing the federal tipped minimum at $2.13/hour, where it remains as of 2026, unchanged for 35 years.
June 2014: Ziosk and Chili's complete the installation of 45,000 tabletop tablets across 823 company-owned Chili's restaurants, the largest tabletop technology rollout in US restaurant history. The tablets allow guests to browse menus, order desserts and beverages, and pay without summoning a server. Industry commentary predicts server displacement. What actually happens: dessert sales rise 20%, average tips increase 15% (the default suggested tip is set at 20%), and Chili's retains its server workforce. The lesson is structural: the tablet handles transaction tasks (ordering, payment), but the server still delivers food, manages the meal's pacing, and provides the human encounter that distinguishes full-service from fast-food. Tasks are automated; the role is not.
McDonald's announces a plan to install self-order kiosks in approximately 2,500 "Experience of the Future" restaurants by end of 2017, adding roughly 1,000 locations per quarter. The kiosks are in quick-service, not full-service dining, waiters and waitresses are not employed at McDonald's, but the rollout triggers wide public concern about server automation in restaurants generally. McDonald's clarifies publicly that it has no plans to eliminate workers via kiosks; the company moves affected cashiers to new roles including tableside food delivery. By 2020, most of the 14,000 US McDonald's locations have kiosks. The kiosk's actual effect: customers order more food and more expensive combinations at kiosks than at the counter, average ticket size rises, and the freed labor is redirected to food preparation and table-service delivery functions.
March-April 2020: COVID-19 closes full-service restaurant dining rooms across the United States. By April, the National Restaurant Association reports that at least 8 million restaurant workers across all categories have been laid off or furloughed. For waiters and waitresses specifically, whose entire compensation model depends on dining-room service, the collapse is near-total: BLS data suggests employment in the waiter/waitress subcategory fell from approximately 2.5 million pre-pandemic to approximately 1 million by April 2020, a 60% decline within six weeks. It is the fastest single-occupation employment collapse in US labor history. By December 2020, approximately 110,000 restaurants had permanently closed, roughly 17% of the industry. The QR code menu, mass-adopted as a sanitary alternative to physical menus, becomes permanent at the majority of full-service restaurants that survive.
The post-COVID labor shortage reshapes server compensation and working conditions. With 8 million restaurant jobs lost and millions of workers having left the industry, restaurants competing for returning servers begin raising base wages above the $2.13 federal floor. Chef's Pencil data shows server wages rose approximately 23% between 2019 and 2022. States with higher subminimum wages (California eliminated the tipped subminimum entirely in 1988; Washington, Oregon, Minnesota, Montana, and Alaska followed) see faster server recovery. The "Great Resignation" disproportionately affects the restaurant industry: quit rates in Accommodation and Food Services peaked at 6.9% in 2021, more than double the national average, driven by burnout, customer abuse, and the income instability of a tip-dependent compensation model.
BLS projects -1% employment for waiters and waitresses 2024-34: the first decade-long outlook showing net decline for the occupation. The projection reflects the durable structural change from COVID: fewer servers per cover, more digital ordering, and continued format-mix-shift toward fast-casual (which employs counter workers, not servers). But the 456,700 projected annual openings are the highest in the food-service category, driven by one of the highest turnover rates in the US economy. The occupation is simultaneously slightly shrinking and generating enormous replacement demand. Federal tipped minimum wage remains $2.13/hour, unchanged since 1991, making the occupation one of the most active fronts in US labor-policy debates about income inequality and the structural poverty of service workers.
Will AI replace waiters and waitresses? What the research says
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.
What's changing day to day for waiters and waitresses
Three parts of your work where AI is already doing real lifting, and what stays yours.
AI is sitting alongside you hereProcess payments using tableside POS terminals or handheld devices (splitting checks, applying discounts, processing contactless and digital wallet payments) while handling the final guest interaction of the dining experience with the warmth and efficiency that influences the tip decision
Process payments using tableside POS terminals or handheld devices (splitting checks, applying discounts, processing contactless and digital wallet payments) while handling the final guest interaction of the dining experience with the warmth and efficiency that influences the tip decision; know that payment UX is the last impression guests carry out the door.[7],[3]
Tableside payment processing via handheld is now standard at most full-service restaurants and eliminates the old walk-away-with-the-card moment, which is both faster and more secure for guests. The payment interaction has become more of a graceful handoff than a friction point when the handheld is in hand. Use that moment to complete the hospitality arc: a genuine "it was great having you" rather than a transactional goodbye. Repeat visit intent is formed in the last minute of a meal.
AI is sitting alongside you herePrepare and set tables before service and clear them between covers: arrange linens, silverware, glassware, and condiments to standard
Prepare and set tables before service and clear them between covers: arrange linens, silverware, glassware, and condiments to standard; clear dishes efficiently between courses; on floors with autonomous bussing robots (Bear Robotics Servi Plus), delegate the heavy bus-tub trips to the robot while personally resetting silver and glassware with the precision and care that signals table readiness to the next guests.[8],[3]
Table setup is your first message to guests before they sit down. Even when a robot clears the previous cover, the reset (fresh water glass placement, menu positioning, napkin fold) is done by human hands because guests notice and judge it. Use the physical reset as a brief mental checkpoint for the table's upcoming guests: did the OpenTable note say they're celebrating something? Is there a dietary flag on the reservation? Preparing the table and preparing your knowledge of the incoming guests is one motion, not two.
AI is sitting alongside you hereUpsell food and beverage add-ons (appetizers, premium proteins, wine pairings, specialty cocktails, desserts) using genuine product knowledge and conversational timing rather than scripted prompts
Upsell food and beverage add-ons (appetizers, premium proteins, wine pairings, specialty cocktails, desserts) using genuine product knowledge and conversational timing rather than scripted prompts; AI platforms (ToastIQ, kiosk upsell engines) automate transactional upsell prompts, but the server who knows the wine list, can describe a dish with conviction, and reads whether the table is in the mood to splurge consistently outperforms any automated recommendation engine on check average and tip percentage.[4],[5]
Study the menu like product knowledge, not memorization. Know three things about every menu item the kitchen is proud of: what makes it special, what it pairs with, and who at the table it's most likely to appeal to. The NRA 2025 data shows kiosks increase average check size through automated upsell prompts, but in full-service dining, the server's live recommendation still outperforms the screen because it comes with credibility, eye contact, and social proof ("this is what I'd order tonight"). Build that product fluency as a professional skill, not a side effect of having worked there a while.
Where waiters and waitresses go next
Natural next steps for someone with your foundation: not exits, evolutions.
- Food Service Managers
- US median pay
- $69,390 (May 2025)
- BLS outlook 2025-35
- +5.8%
- First-Line Supervisors of Food Preparation and Serving Workers
- US median pay
- $44,080 (May 2025)
- BLS outlook 2025-35
- +5.4%
- Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop
- US median pay
- $31,200 (May 2025)
- BLS outlook 2025-35
- +3.4%
- Retail Salespersons
- US median pay
- $35,410 (May 2025)
- BLS outlook 2025-35
- -0.3%
What each move takes
Food Service Managers
The path from server to Food Service Manager is achievable over several years of progressive FOH experience, often through the First-Line Supervisor step above. Food Service Managers run the full operation: P&L responsibility, vendor relationships, hiring, training programs, compliance, and brand standards. The NRA 2025 report identifies technology fluency (managing AI-powered POS platforms, reservation systems, and labor-scheduling tools) as an increasingly important management competency, meaning servers who develop deep system knowledge alongside their hospitality skills are building manager credentials simultaneously. CRI is higher because food service management is less exposed to task-level automation: the role is coordination, judgment, and relationship management rather than execution.
- · Restaurant P&L fundamentals: reading a daily food-cost and labor-cost report, identifying waste and margin leakage
- · Hiring and onboarding management: writing job descriptions, screening for service aptitude, designing 30/60/90 day onboarding
- · Vendor management: purchase order process, invoice reconciliation, and negotiating pricing with food and beverage distributors
- · Technology platform administration: managing POS menu updates, reservation system settings, and labor-scheduling software
- · Regulatory compliance: food safety manager certification (ServSafe Manager), liquor licensing compliance, and health department inspection readiness
How has the work of waiters and waitresses changed since 1827?
The tools that defined the work, one line per era. Select an era to see how it reshaped the work.
White-cloth service + handwritten checks (Delmonico's fine-dining standard)
In the Delmonico's era, waiter equipment was cloth: a white linen folded over the forearm to protect both hand and dish, a small notebook or mental memory for orders, and the dexterity to carry multiple plates through a crowded room without disaster. The check was handwritten at the table; the kitchen communicated via verbal call or handwritten slip. Silver-service technique (presenting dishes from the left, removing from the right, refilling glasses without interrupting conversation) was imported from European hotel training and became the standard of "fine dining" that American waiters emulated. The customer-per-server ratio was generous by modern standards: one server might attend two or three tables in a formal setting.
Harvey House standardized chain training: the first service protocol system
Fred Harvey's innovation was not the food or the decor but the system. Every Harvey Girl received the same training, wore the same uniform (black dress, white apron, white ribbon), and executed the same service protocols across many stations from Kansas to California. The Atchison, Topeka and Santa Fe Railroad funded the dining cars; Harvey supplied the staff and the standards. A customer could travel thousands of miles and expect the same coffee service at every stop. This was the invention of the service protocol: the scripted, trainable, reproducible set of behaviors that today underlies chain-restaurant training across the industry. The tools were minimal (a tray, a pot, a pad), but the system was the technology.
Effect on the workHarvey replaced male waiters with female staff throughout the 1880s, arguing (correctly, in his experience) that Harvey Girls were more reliable, better mannered, and more trainable. Roughly 100,000 women worked as Harvey Girls between 1883 and the 1950s. The system helped open the West to women workers outside domestic service for the first time.
Automat + cafeteria self-service (Horn & Hardart, 1902): the first server-displacement technology
In 1902, Horn & Hardart opened the first American Automat at 818 Chestnut Street in Philadelphia, using coin-operated vending compartments imported from Berlin. The 1912 New York Times Square location fed thousands daily at nickel prices. At its peak Horn & Hardart was the world's largest restaurant chain, with many locations serving hundreds of thousands of meals per day: using no servers at all. The Automat was the first serious technology displacement for waiters and waitresses: it offered hot food, cheap prices, and the dignity of self-service without the social discomfort of tipping. The cafeteria model that followed (Howard Johnson's lunch counters, Woolworth's soda fountains) embedded server-free or counter-service formats into everyday dining. That the waiter workforce grew rapidly throughout this same period (1900-1940) despite the Automat's rise is the first iteration of the core pattern: displacement technologies expand the market even as they substitute in a specific segment.
Carbon-copy check pad + electromechanical cash register (diner-era order management)
The diner era and the casual-dining chain expansion of the 1950s-1980s standardized the server's toolkit: a numbered check pad with carbon copies (one for the kitchen, one for the customer, one for the register reconciliation), a mechanical cash register that summed the check, and a tray for carrying four to six plates at a time. The skills were tactile, memorizing tables, carrying multiple plates without a tray, managing the "rail" of waiting orders with a mental map of who ordered what. The 1966 FLSA extension of minimum-wage coverage to restaurant workers arrived simultaneously with the expansion of national casual-dining chains (Denny's, IHOP, TGI Fridays, Howard Johnson's) that established the American version of the role: a server covering five to eight tables on a shift, compensated primarily through tips, with tables turning over every hour or so.
Aloha POS / Micros POS + handheld server terminals (digital order entry)
Aloha Technologies (founded 1986) and Micros Systems (founded 1977, broadly adopted in full-service restaurants through the 1990s) replaced the carbon-copy check pad with a point-of-sale terminal: a touchscreen at the server station where orders were entered, routed electronically to kitchen display screens, and tracked for billing. For the server, this meant faster order transmission (no shouting across a pass), instant check printing, and credit-card swipe at a fixed terminal. The POS did not change the interpersonal core of the job (taking orders, reading the table, managing the pacing of a meal) but it eliminated the math (the computer summed the check) and the kitchen relay (the system managed it). OpenTable launched in 1999, digitalizing the host-stand reservation book and allowing servers to see the guest flow before the shift started.
Ziosk tabletop tablets + pay-at-table (Chili's 2014, 45,000 tablets nationwide)
In June 2014, Ziosk and Chili's completed the largest tabletop tablet rollout in US restaurant history: 45,000 tablets across hundreds of company-owned Chili's locations. The device sat on the table and allowed guests to browse the menu, order drinks and desserts, play games, and pay the check, without summoning a server. By 2014, more than 75,000 Ziosk tablets were in over 1,350 restaurants nationally, serving tens of millions of guests per month. The predicted narrative was automation displacing servers. Servers kept their jobs but changed what they spent them doing. The tabletop tablet was the first modern technology that plausibly demonstrated the difference between automating a server's tasks and automating a server's role.
Effect on the workZiosk adoption at Chili's and other casual chains did not reduce server headcounts in the short term; it shifted the composition of server work from transaction tasks (ordering, check delivery, payment processing) toward hospitality tasks (recommendations, food delivery, complaint resolution). Cover-to-server ratios did not measurably change in the Chili's deployment.
Toast handheld POS + delivery platform integration (GrubHub, DoorDash)
Toast (founded 2013) brought the POS to the table via a handheld device: servers entered orders and accepted payment without returning to a fixed terminal, reducing round-trip time and allowing quicker table turns. Simultaneously, GrubHub (national scale 2013) and DoorDash (founded 2013) created a delivery-first channel that required a different category of labor: kitchen workers and gig drivers, not servers. Full-service restaurants that added third-party delivery did not typically reduce server headcounts, as delivery orders came from the kitchen side, not the dining room.
COVID QR menus + contactless payment: permanent shift in table-service workflow
In March 2020, state health authorities closed full-service restaurant dining rooms across the US, and when they reopened (first at reduced capacity, then progressively) operators needed to eliminate shared physical menus. A large share of operators implemented contactless or mobile payment as a pandemic safety measure; and the National Restaurant Association found that large share of restaurants that adopted QR menus kept them permanently after health restrictions lifted. The QR menu permanence is significant because it shifted the menu-presentation task, previously a ritual of physical handoff and a social cue to the customer that their server was attentive, into a passive self-service action. Servers retained the order-delivery, drink-management, and hospitality functions; the QR menu eliminated a specific workflow beat. The net effect by 2023: fewer servers are needed per cover than in 2019, which is why employment has not fully recovered to pre-pandemic levels despite strong dining-out demand.
Effect on the workQR menus and contactless payment contributed to a permanent structural reduction in server-to-cover ratios post-COVID. BLS employment data shows 2.3 million waiters and waitresses in 2024 vs. 2.5 million pre-pandemic: a durable reduction that has not fully recovered despite strong restaurant industry demand.
AI phone-ordering agents + AI scheduling and tip analytics tools
By 2024, a new category of AI tools had entered the full-service restaurant space targeting the server's upstream and downstream functions. AI phone-ordering agents (used initially for takeout and delivery phone orders) began reaching into casual-dining reservation and order-ahead workflows, handling the pre-arrival ordering that previously required a host or manager. Toast's AI-assisted analytics dashboard surfaced shift-level tip data, busiest-section predictions, and menu-item profitability insights, turning the manager's historical intuition into a data-driven tool. These are augmentation tools for the operator layer, not for the server. No credible deployed product in 2024-2025 had automated the in-dining-room service function of a full-service restaurant: the act of reading a table, managing a meal's pacing, handling a complaint, or building the interpersonal rapport that drives return visits and tip income.
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Browse all rolesWaiters and Waitresses employment and pay by year
In other countries
The latest figure each country's statistics agency publishes for this job. Each uses its own occupation definition, survey basis and currency, so the numbers are not directly comparable with each other or with the US figures.
Canada (NOC 65200)
- Employment, 2020
- 127,700, Statistics Canada Census 2021 Official statistic Report an errorStatistics Canada Census of Population 2021: number of persons with employment income in NOC 65200 Food and beverage servers, Canada, reference year 2020. A recipients basis (anyone with employment income during the year), slightly broader than a point-in-time employed count. Statistics Canada Open Licence.
- Median pay, 2020
- C$23,800, Statistics Canada Census 2021 Official statistic Report an errorStatistics Canada Census of Population 2021 (Table 98-10-0586): median employment income for NOC 65200 Food and beverage servers, Canada, reference year 2020, full-year full-time workers (the basis comparable to the US OEWS full-time median). Statistics Canada Open Licence.
United Kingdom (UK SOC 9264)
- Employment, 2025
- 146,000, ONS ASHE 2025 Official statistic Report an errorONS Annual Survey of Hours and Earnings (Table 14): employee jobs in SOC 9264 Waiters and waitresses, United Kingdom, 2025 (ASHE "number of jobs", thousands x1000; excludes self-employment). Open Government Licence v3.0.
- Median pay, 2025
- £10,000, ONS ASHE 2025 Official statistic Report an errorONS Annual Survey of Hours and Earnings (Table 14.7a): median gross annual pay for all employee jobs in SOC 9264 Waiters and waitresses, United Kingdom, 2025. Open Government Licence v3.0.
Australia (ANZSCO 4315)
- Employment, 2025
- 129,900, ABS Labour Force Survey Official statistic Report an errorABS Labour Force Survey (Detailed), table EQ08: employed persons in ANZSCO 4315 Waiters, national (summed across sex and state/territory), annual average of 4 quarterly estimates.
- Median pay, 2025
- A$69,992, ABS Employee Earnings May 2025 Official statistic Report an errorAnnualised (x52) from A$1,346 median weekly earnings. ABS Survey of Employee Earnings and Hours, May 2025: median pay for full-time non-managerial employees paid at the adult rate, before tax. Surfaced via the Jobs and Skills Australia occupation profile.
View all 29 years of cited US data, each linked to its source
| Year | US employment | Annual pay (median unless marked) | Source | Report |
|---|---|---|---|---|
| 1900 | 200,000 | n/a | Est., IPUMS USA Researched context | Report |
| 1940 | 540,000 | n/a | Est., FRASER / St. Louis Fed Researched context | Report |
| 1966 | n/a | $2,100 | Est., DOL Researched context | Report |
| 1970 | 1,100,000 | n/a | Est., BLS Monthly Labor Review Researched context | Report |
| 1991 | n/a | $8,840 | Est., CEPR Researched context | Report |
| 2000 | 2,008,760 | n/a | BLS OEWS 2000 Official statistic | Report |
| 2003 | 2,125,100 | $14,100 | BLS OEWS May 2003 Official statistic | Report |
| 2004 | 2,219,850 | $14,050 | BLS OEWS May 2004 Official statistic | Report |
| 2005 | 2,274,770 | $14,200 | BLS OEWS May 2005 Official statistic | Report |
| 2006 | 2,312,930 | $14,850 | BLS OEWS May 2006 Official statistic | Report |
| 2007 | 2,357,040 | $15,850 | BLS OEWS May 2007 Official statistic | Report |
| 2008 | 2,371,750 | $16,660 | BLS OEWS May 2008 Official statistic | Report |
| 2009 | 2,302,070 | $17,690 | BLS OEWS May 2009 Official statistic | Report |
| 2010 | 2,244,480 | $18,330 | BLS OEWS May 2010 (employment) Official statisticBLS OEWS 2010 (pay) Official statistic | Report |
| 2011 | 2,289,010 | $18,570 | BLS OEWS May 2011 Official statistic | Report |
| 2012 | 2,332,020 | $18,540 | BLS OEWS May 2012 Official statistic | Report |
| 2013 | 2,403,960 | $18,590 | BLS OEWS May 2013 Official statistic | Report |
| 2014 | 2,445,230 | $18,730 | BLS OEWS May 2014 Official statistic | Report |
| 2015 | 2,505,630 | $19,250 | BLS OEWS May 2015 Official statistic | Report |
| 2016 | 2,564,610 | $19,990 | BLS OEWS May 2016 Official statistic | Report |
| 2017 | 2,584,220 | $20,820 | BLS OEWS May 2017 Official statistic | Report |
| 2018 | 2,582,410 | $21,780 | BLS OEWS May 2018 Official statistic | Report |
| 2019 | 2,579,020 | $22,890 | BLS OEWS May 2019 Official statistic | Report |
| 2020 | 1,944,240 | $23,740 | BLS OEWS May 2020 Official statistic | Report |
| 2021 | 1,804,030 | $26,000 | BLS OEWS May 2021 Official statistic | Report |
| 2022 | 2,122,210 | $29,120 | BLS OEWS May 2022 Official statistic | Report |
| 2023 | 2,237,850 | $31,940 | BLS OEWS May 2023 Official statistic | Report |
| 2024 | 2,302,690 | $33,760 | BLS OEWS May 2024 Official statistic | Report |
| 2025 | 2,270,910 | $35,230 | BLS OEWS May 2025 Official statistic | Report |
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