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Bussers and barbacks

Official title Dining Room and Cafeteria Attendants and Bartender Helpers (SOC 35-9011)

Also called Busser, Bus person, Bus boy, Dining room attendant, Barback

In brief

In May 2025, BLS counted 542,750 US bussers and barbacks, with median pay of $33,980 a year. The earliest figure here is an estimate of 80,000 from 1900, not measured the same way as today's count. The last full technology era for bussers and barbacks: POS kitchen display + handheld runner tickets, 1985 to 2017.

What the sources say

Official outlook

BLS projects employment to grow 5.3% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

  • 0% of this job's tasks are exposed to large language models. Not a forecast of job losses. Eloundou and others, 2023
  • 0.91 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 0.91. BLS counted 409,700 of these jobs in May 2013 and 542,750 in May 2025 (+32%, a change derived by Future History).

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
APA

Future History. (2026, October 11). Bussers and barbacks: jobs and pay since 1900 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/35-9011

Chicago

Future History. "Bussers and barbacks: 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/35-9011.

BibTeX

@misc{futurehistory_35_9011, author = {{Future History}}, title = {Bussers and barbacks: jobs and pay since 1900}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/35-9011}}, 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.

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1850187519001925195019752000now
2026
Known then as Dining room boy / table-boy (Delmonico's fine-dining era)
Known then as Dining room helper / back waiter (Harvey House and railroad chain service)
Known then as Busboy / bus girl / cafeteria attendant (diner and cafeteria era)
Known then as Busboy / bar-back / food runner (casual-dining chain expansion)
Known then as Server assistant / dining room attendant / bar-back (pre-SOC formal title)
Known then as Dining Room and Cafeteria Attendants and Bartender Helpers (BLS SOC 35-9011)
Known today as Dining Room and Cafeteria Attendants and Bartender Helpers (BLS SOC 35-9011)
Projected to still be called Dining Room and Cafeteria Attendants and Bartender Helpers (BLS SOC 35-9011)
Data from the May 2025 survey
US Employment
543K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$33,980
Est.

≈ $33,109 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1827

Delmonico's opens at 23 William Street in lower Manhattan: America's first establishment operating as a true restaurant with à la carte service, individual tables, a French-English menu, and trained front-of-house staff. The brigade structure Delmonico's imports from European hotel service establishes a hierarchy that places a junior dining-room attendant below the head waiter: this person clears courses, refills water, carries heavy silver serving pieces, and resets table covers between parties. Fred Harvey himself began his own career as this person, a busboy in a New York restaurant in the 1850s, before rising to waiter, line cook, and eventually restaurateur. The busser role is old enough to have produced one of the most consequential restaurant operators in American history.

Beat · 1876

Fred Harvey opens his first depot dining room in Topeka, Kansas, under contract with the Atchison, Topeka and Santa Fe Railroad: the beginning of the first national restaurant chain in the United States. Harvey's operation runs to a train schedule: doors open when the train pulls in, service must be complete before it departs. The twenty-minute service window requires that clearing and resetting happen in parallel with service, not sequentially: the dining room attendant function becomes time-critical in a way it had never been in leisurely fine dining. By 1901, Harvey's 47 restaurants and 30 dining cars serve over one million meals per month during WWII. The Harvey system is the first demonstration that dining room support labor can be systematized, timed, and scaled across a national network.

Beat · 1902

Horn & Hardart opens the first American Automat at 818 Chestnut Street in Philadelphia: a coin-operated, server-free restaurant that feeds hundreds of thousands daily at its peak across 80 New York City locations. The Automat is the first major technology predicted to eliminate food-service support roles. What actually happens: the Automat employs "invisible kitchen workers" who quickly refilled empty compartments from behind the wall, plus dining-room clearing staff who keep the seating area functional for the constant turnover of urban lunch traffic. The Automat eliminates servers, but it increases the density of dining room support work, more covers per hour, faster turns, higher volume of clearing. The support function adapts to the format rather than disappearing from it.

Beat · 1946

The National School Lunch Program is established by Congress (Public Law 79-396), providing federally subsidized meals to school children. By 1970, the program serves 20 million children daily across approximately 80,000 schools. Each school lunch program requires cafeteria attendants to clear trays, wipe tables, manage serving lines, and maintain the cafeteria environment, creating a large institutional demand for the cafeteria attendant function outside of commercial restaurants. This institutional sector (schools, hospitals, government and corporate cafeterias) provides an employment floor for SOC 35-9011 workers that is relatively insensitive to restaurant-industry cycles: a school cafeteria attendant has a job whether or not the restaurant industry is booming.

Beat · 2017

Bear Robotics is founded in May 2017 by John Ha, a former Google software engineer, after he purchased a restaurant in Redwood City, California and experienced firsthand the difficulty of staffing the food-runner position during a labor shortage. Ha's insight: the food-runner task (carrying trays from the kitchen pass to the table) is highly repetitive, spatially bounded, and does not require conversation, the three conditions most favorable to robotic substitution. The company's first robot, "Penny," is tested at Ha's restaurant; the production version, "Servi," begins commercial deployment in 2019-2020. By January 2022, Bear Robotics reports that deployed Servi units have collectively traveled 247,500 miles. SoftBank led a $32M Series A in 2020; the company raised an $81M Series B in 2022. By 2024, Servi is operating in Denny's, Chili's, Olive Garden, and dozens of other casual-dining chains in the US and South Korea. Ha's insight was correct about the task; the deployment experience revealed the constraints: Servi requires a human to load each tray at the kitchen pass, cannot navigate stairs or highly irregular floor layouts, and cannot interact with guests. The robot handles one sub-task of the food runner's role, not the role itself.

Beat · 2020

March-April 2020: COVID-19 closes full-service restaurant dining rooms across the United States. Dining room attendants and bar-backs are the front-of-house workers most completely dependent on in-person service, unlike kitchen workers who can pivot to delivery preparation, a busser has nothing to bus when the dining room is empty. The National Restaurant Association reports that 8 million restaurant workers across all categories were laid off or furloughed by April 2020; sales were down 34% on average even by August 2020; nearly 100,000 restaurants had permanently or long-term closed by September 2020. For the dining room attendant specifically, the collapse was acute: estimates from BLS CPS data for food service support workers suggest employment fell approximately 50% from pre-pandemic levels at the April 2020 trough. Unlike server jobs, which benefited from delivery-platform work in some markets, there was no delivery-era pivot for a busser. The occupation's recovery to 522,010 by 2024 (BLS OEWS), above the pre-pandemic peak, is evidence of the structural durability of the role, not evidence that the COVID disruption was mild.

Beat · 2024

BLS projects +6.3% employment growth for dining room and cafeteria attendants and bartender helpers 2024-34 (from 527,400 to 560,600) driven primarily by full-service restaurant expansion (307,500 → 331,400 within that sector). Projected annual openings of 99,600 reflect both new jobs and high turnover; this occupation has one of the highest turnover rates in the US food service sector, driven by the entry-level wage structure, physically demanding work, and the role's function as a stepping stone to server and bartender positions. The BLS projection does not model robot displacement: it models productivity-adjusted demand under current technology. Bear Robotics Servi units are operating in tens of thousands of casual-dining restaurant locations by 2024, but operator reports consistently describe them as labor-assist tools rather than headcount reducers. The occupation enters 2024 at its highest-ever recorded employment level.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace bussers and barbacks? 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 published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+5.3%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 35-9011 (Dining room and cafeteria attendants and bartender helpers): 546.6 thousand jobs in 2025, projected 575.5 thousand in 2035, a change of +28.9 thousand (+5.3%). Matrix employment counts all jobs in the occupation, including self-employed workers (0.1% of this occupation in 2025). The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Frey & Osborne (2013), "The Future of Employment"
2013 study · Probability of computerisation (2013 model)
91%
probability
What this measures

Published appendix value for SOC 2010 35-9011 Dining Room and Cafeteria Attendants and Bartender Helpers: probability of computerisation 0.91, rank 555 of 702 (rank 1 is least computerisable). Frey and Osborne estimated in 2013, with a Gaussian-process classifier on O*NET variables, how likely the whole occupation is to be technically automatable over "some unspecified number of years, perhaps a decade or two". It is a probability for the occupation, not a share of tasks and not a forecast of jobs lost.

Official statisticReport an error
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
0%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 35-9011.00 Dining Room and Cafeteria Attendants and Bartender Helpers. Shown: human-rated β = 0, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0 and γ (all LLM-assisted) 0; GPT-4-rated β 0. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for bussers and barbacks

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereCarry food trays or individual dishes from the kitchen pass or food counters to the correct dining tables or cafeteria stations

Carry food trays or individual dishes from the kitchen pass or food counters to the correct dining tables or cafeteria stations; confirm dish placement with guests; communicate any substitutions or delays from the kitchen to the server.[1],[3]

Tools picking this up
Where your edge is

Take ownership of the delivery confirmation step: learn every table’s order so you can deliver with confidence and correct robot-routing errors before guests notice. Robots need a human to verify the hand-off.

AI is sitting alongside you hereClear, wipe, and reset dining tables between guest turns: remove dishes, glassware, and soiled linens

Clear, wipe, and reset dining tables between guest turns: remove dishes, glassware, and soiled linens; replace tablecloths or wipe hard-surface tables; reset place settings with clean silverware, glassware, and napkins in preparation for the next cover.[1],[3]

Tools picking this up
Where your edge is

Work ahead of the robot: identify tables that are finishing before they ask for the check, coordinate with servers on timing, and handle the social moments (thanking guests, noting spills that need management attention) that robots cannot navigate.

AI is sitting alongside you hereSupport bar operations as a barback: wash and polish glassware, restock ice bins and speed-rail liquors, cut and prep garnishes, remove empty bottles, and keep the bar area clean during service so the bartender can focus on guests.

Support bar operations as a barback: wash and polish glassware, restock ice bins and speed-rail liquors, cut and prep garnishes, remove empty bottles, and keep the bar area clean during service so the bartender can focus on guests.[1],[6]

Tools picking this up
Where your edge is

Barback experience is the fastest on-ramp to bartending. Leverage the time freed by glasswasher automation to observe and assist the bartender more directly, learning drink preparation and order pacing.

Where bussers and barbacks go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

Experienced dining room and cafeteria attendants who develop floor leadership habits (reading service flow, training new staff, managing par levels under pressure) are natural candidates for shift supervisor and front-of-house lead roles. This is the most direct upward path within food service that doesn't require a credential. The supervisory layer is more resilient to robot substitution because it requires scheduling judgment, conflict resolution with staff and guests, and coordinating across the kitchen-floor interface.

What you'd add
  • · Food handler certification and ServSafe Food Manager credential
  • · Scheduling and labor-cost basics (reading a labor report, managing overtime)
  • · Conflict resolution and team communication under service pressure
  • · Inventory and ordering fundamentals (par levels, waste tracking)
What it takesSome new skills to pick up
Tools of the era

How has the work of bussers and barbacks changed since 1827?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Bus tub + tray: manual clearing and resetting (Delmonico's-era fine dining)

    The tools of the dining room attendant in the Delmonico's era were simple and physical: a large tray for carrying multiple plates from kitchen to table, a rectangular basin for clearing dirty dishes (the "bus tub," from which the term "busboy" derives), a damp cloth for crumbing tables between courses, and pitchers for water service. The skill was entirely physical: balance, speed, and spatial awareness in a crowded dining room. In fine-dining establishments like Delmonico's, the junior dining-room staff operated on a strict brigade hierarchy: the senior waiter owned the guest relationship; the dining room boy cleared, reset, and carried. This division of labor has not materially changed in centuries; what has changed is the volume and speed expected.

  • Harvey House standardized service protocols: the first timed support-role system

    Fred Harvey's railroad dining rooms, first opened in 1876, introduced the first standardized service protocol for front-of-house support work in the United States. Harvey Houses operated on a fixed window, trains stopped for many minutes, which meant that clearing and resetting had to happen to a schedule, not at the server's discretion. Harvey began his own career as a busboy in a New York restaurant before advancing to waiter; he imported that brigade structure into his railroad dining rooms. The Harvey system demonstrated that the food-runner and table-clearing functions could be systematized, timed, and replicated across locations: the intellectual precursor to the chain-restaurant operations manuals that would standardize the role in the 1980s.

    Effect on the work

    Harvey Houses at their 1901 peak operated many restaurants, several hotels, and many dining cars. The support staff structure (dining room helpers alongside Harvey Girl waitstaff) established a labor-efficiency model that casual-dining chains would formalize decades later.

  • Automat and cafeteria self-service (Horn & Hardart, 1902): partial displacement, not replacement

    In 1902, Horn & Hardart opened the first American Automat at 818 Chestnut Street in Philadelphia, eliminating waiters entirely for its quick-lunch format. At its peak Horn & Hardart fed hundreds of thousands daily across dozens of New York locations, each requiring behind-the-counter and dining-room clearing staff. The cafeteria model that spread through the 1920s-1950s (Stouffer's, Morrison's, and the National School Lunch Program's institutional cafeterias) also reduced the need for table-side servers, but it increased the need for tray-clearing and sanitation support staff who kept the serving lines and dining areas clean. The Automat's lesson for the dining room attendant is the same as for the waiter: self-service formats shift the job rather than eliminating it. The clearing function becomes higher-volume (more covers, faster turns) rather than disappearing.

  • Conveyor dishwasher + standardized bus station: industrializing the clearing function

    The industrial conveyor dishwasher, which became standard equipment in high-volume restaurant and cafeteria kitchens in the 1950s, created a new logistical task for the dining room attendant: loading the conveyor efficiently. A busser who delivered dishes scraped and racked onto a conveyor could clear a table in under two minutes and have the dishes clean in four; the same busser stacking loosely in a hand-sink kitchen took twice as long. Operators began designing bus stations, storage carts positioned in specific dining room positions, to minimize the walk from table to dish station and back. The standardized bus station (cart with bus tubs, water pitcher station, bread and condiment refill zone) became the physical infrastructure of the role from the 1960s onward. Chain casual dining (Denny's, IHOP, TGI Fridays, Applebee's) codified this layout in operations manuals with precise time-per-table standards.

  • POS kitchen display + handheld runner tickets: digital order routing to food runners

    As restaurant point-of-sale systems (Aloha, Micros, Toast) moved from paper to digital, the food-runner role acquired a new tool: the kitchen display screen or runner ticket. In a restaurant with a POS-fed KDS, the food runner no longer relied on a verbal call from the expo (expediter) or a paper ticket stapled to the order; the screen showed which table, which items, and which modifier, reducing miscommunication between kitchen and dining room. For the bar-back specifically, POS integration with bar inventory systems meant predictable restocking signals: when a bottle of well vodka scanned below par, the system flagged it. Neither technology changed the physical core of the role, carrying things from one place to another, but both improved accuracy and reduced the walk-back-to-kitchen correction rate.

  • Bear Robotics Servi: autonomous tray-delivery robot (founded May 2017, mass deployment 2022+)

    In May 2017, former Google software engineer John Ha founded Bear Robotics in Redwood City, California, with the explicit goal of automating the food-runner function in casual-dining restaurants. The company's first robot, "Penny," was tested at Ha's own Willow Tree restaurant in Redwood City. The production version, "Servi," is a three-tray autonomous delivery robot that navigates restaurant floors using LiDAR and cameras, carrying food from the kitchen pass to the table. By 2022, Servi robots were logging significant mileage milestones (247,500 miles of total travel as of January 2022); by 2024 the company had deployed units across Denny's, Chili's, Olive Garden, and dozens of other casual-dining chains in the United States and South Korea. SoftBank led a $32M Series A in 2020; the company then raised an $81M Series B in 2022. The deployment reality differs materially from the displacement narrative: Servi carries trays to tables but cannot load itself (a human at the kitchen pass loads each tray), cannot navigate stairs, cannot handle highly irregular floor layouts, cannot interact with guests when they ask "which is the salmon?", and cannot bus the dirty dishes back. The robot handles one sub-task of the food runner's job, not the job itself. Chains deploying Servi have reported it primarily frees the food runner's hands for higher-value interactions rather than reducing headcount.

    Effect on the work

    Casual-dining chains deploying Servi (Denny's, Chili's, Olive Garden) have reported using robots primarily to assist rather than replace dining room attendants: the robot carries food while the human loads it and manages guest interactions. No major chain has reported headcount reductions attributable to Servi deployment as of 2024; the technology is more accurately described as a labor-assist tool in a labor-scarce market than as a displacement technology.

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Dining Room and Cafeteria Attendants and Bartender Helpers employment and pay by year

On record since1827
Latest US employment542,750 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$33,980 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+5.3% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 28 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
190080,000n/aEst., IPUMS USA Researched contextReport
1940200,000n/aEst., FRASER / St. Louis Fed Researched contextReport
1966n/a$1,900Est., DOL Researched contextReport
1970320,000n/aEst., BLS Monthly Labor Review Researched contextReport
2000435,500$13,580BLS OEWS 2000 Official statisticReport
2003393,500$14,570BLS OEWS May 2003 Official statisticReport
2004390,980$14,770BLS OEWS May 2004 Official statisticReport
2005391,320$15,040BLS OEWS May 2005 Official statisticReport
2006401,790$15,310BLS OEWS May 2006 Official statisticReport
2007401,070$16,040BLS OEWS May 2007 Official statisticReport
2008416,410$16,740BLS OEWS May 2008 Official statisticReport
2009402,020$17,700BLS OEWS May 2009 Official statisticReport
2010390,920$18,190BLS OEWS May 2010 Official statisticReport
2011391,290$18,420BLS OEWS May 2011 Official statisticReport
2012395,750$18,500BLS OEWS May 2012 Official statisticReport
2013409,700$18,610BLS OEWS May 2013 Official statisticReport
2014410,460$18,760BLS OEWS May 2014 Official statisticReport
2015412,830$19,280BLS OEWS May 2015 Official statisticReport
2016423,080$20,200BLS OEWS May 2016 Official statisticReport
2017436,730$21,160BLS OEWS May 2017 Official statisticReport
2018455,700$22,270BLS OEWS May 2018 Official statisticReport
2019477,270$23,470BLS OEWS May 2019 Official statisticReport
2020374,940$25,010BLS OEWS May 2020 Official statisticReport
2021336,970$27,170BLS OEWS May 2021 Official statisticReport
2022439,770$29,120BLS OEWS May 2022 Official statisticReport
2023n/a$31,180BLS OEWS May 2023 Official statisticReport
2024522,010$32,670BLS OEWS May 2024 Official statisticReport
2025542,750$33,980BLS OEWS May 2025 Official statisticReport
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