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Restaurant hosts and hostesses

Official title Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop (SOC 35-9031)

Also called Host, Hostess, Greeter, Dining room host, Restaurant host

In brief

In May 2025, BLS counted 432,690 US restaurant hosts and hostesses, with median pay of $31,200 a year. Of the BLS counts since 2003, the May 2025 count is the highest. The earliest figure here is an estimate of 45,000 from 1950, not measured the same way as today's count. The last full technology era for restaurant hosts and hostesses: AI-assisted reservation platforms, 2020 to 2024.

What the sources say

Official outlook

BLS projects employment to grow 3.4% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

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 .

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APA

Future History. (2026, October 11). Restaurant hosts and hostesses: jobs and pay since 1950 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/35-9031

Chicago

Future History. "Restaurant hosts and hostesses: jobs and pay since 1950." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/35-9031.

BibTeX

@misc{futurehistory_35_9031, author = {{Future History}}, title = {Restaurant hosts and hostesses: jobs and pay since 1950}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/35-9031}}, 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.

drag to travel through time
1850187519001925195019752000now
2026
Known then as Headwaiter / Dining Room Steward (hotel dining era)
Known then as Headwaiter / Maitre d'Hotel (formal restaurant era)
Known then as Hostess (tea room and casual dining era, women entering role)
Known then as Host / Hostess (chain restaurant expansion era)
Known then as Host / Hostess / Greeter (casual dining standardization)
Known then as Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop (BLS SOC 35-9031)
Known today as Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop (BLS SOC 35-9031)
Projected to still be called Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop (BLS SOC 35-9031)
Data from the May 2025 survey
US Employment
433K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$31,200
Est.

≈ $30,400 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1851

Wilson's Ladies and Gentlemen's Confectionery in Boston employs "lady attendants" to welcome guests -- one of the first documented instances of a formal female greeting and seating role in American public dining. This marks the beginning of the long displacement of the male headwaiter by female hosts in mid-market and tea room settings, a transition that would accelerate through the Prohibition era of the 1920s.

Beat · 1904

L.D. Houston is photographed as headwaiter in New York -- a representative of the generation of Black men who built the professional dining-room hosting function in American hotels and fine restaurants from the 1840s through the early 1900s. By 1904 this generation was being systematically displaced: racist hiring practices and violent intimidation were pushing Black men out of the premium hotel dining rooms they had staffed for decades, leading many to seek work abroad (Houston went to Hong Kong). The restaurant-ingthroughhistory.com account of this transition documents a pattern of racial exclusion that reshaped who held hosting roles for most of the 20th century.

Beat · 1920

Tea rooms reach peak popularity during Prohibition (1920-1933). With all-female staffs, they introduce the hostess as a distinct social function: often a society woman hired to attract her social circle as clientele. This demographic shift feminized the restaurant greeting and seating role in the middle market just as male headwaiters were being displaced in fine dining by immigrant European maitre d's. The tea room hostess model became the template for the chain restaurant hostess position that would dominate the second half of the 20th century.

Beat · 1940

Grace E. Smith becomes president of the National Restaurant Association in 1940 -- the first woman to lead the trade group. Her presidency reflected the degree to which women had become central to restaurant operations across all front-of-house functions, including hosting and service management, over the preceding two decades. By 1940 women represented roughly 60% of the dining public (up from 20% before World War I) and a substantial share of front-of-house staff.

Beat · 1998

OpenTable is founded on July 2, 1998 in San Francisco by Chuck Templeton. It introduces the first real-time online reservation system for restaurants, replacing phone-and-ledger reservations with software-managed guest lists accessible to diners online. OpenTable's growth was gradual at first -- it took years to reach critical mass in any single city -- but by the mid-2000s it had become the standard reservation platform for full-service restaurants in major US markets. The transition from paper reservation book to software changed the skill profile of hosting, making platform proficiency a baseline requirement.

Beat · 2020

COVID-19 forces the closure of dining rooms across the United States beginning in March 2020. The restaurant industry loses more than 8 million jobs; the eating and drinking place sector finishes 2020 nearly 2.5 million jobs below its pre-COVID level. Hosts and hostesses are among the first eliminated when dining rooms close and among the last to be rehired as restaurants reopen under capacity restrictions. The pandemic accelerated two trends already underway: the shift toward delivery and takeout (which does not require hosts) and the adoption of contactless digital platforms (QR code menus, online waitlist check-ins) that reduced the functional surface area of the host role.

Beat · 2025

Yelp launches Yelp Host in October 2025 at $149-$399/month per restaurant location -- the first major consumer-facing tech brand to enter the voice AI phone agent market for restaurant hosting. The product answers all inbound phone calls, takes and modifies reservations via Yelp Guest Manager integration, quotes wait times, and sends SMS waitlist links. Hostie AI, a competing platform, reports that early adopters are having approximately 84% of routine calls handled autonomously. This marks the beginning of the commercial market for AI phone agents in restaurant hosting -- a distinct phase from the AI-assisted reservation platforms (SevenRooms, OpenTable) that had been automating back-end reservation optimization for several years.

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 restaurant hosts and hostesses? 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
+3.4%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 35-9031 (Hosts and hostesses, restaurant, lounge, and coffee shop): 444.2 thousand jobs in 2025, projected 459.5 thousand in 2035, a change of +15.3 thousand (+3.4%). Matrix employment counts all jobs in the occupation, including self-employed workers (2% 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.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
32.9%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 35-9031.00 Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop. Shown: human-rated β = 0.329, 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) 0.2 and γ (all LLM-assisted) 0.457; GPT-4-rated β 0.229. 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 restaurant hosts and hostesses

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

AI is sitting alongside you hereHandle incoming phone calls for reservations, cancellations, modifications, and general inquiries (hours, parking, large-party policies, dietary accommodations)

Handle incoming phone calls for reservations, cancellations, modifications, and general inquiries (hours, parking, large-party policies, dietary accommodations); enter reservation details into the reservation platform accurately, capturing party size, special requests, and contact information; in restaurants using AI phone agents (Yelp Host, Slang AI), monitor the AI call log, handle escalated calls the AI flags, and configure the system with current specials and policy updates.[2],[3],[8]

Tools picking this up
Where your edge is

As AI phone agents handle routine calls, your comparative advantage shifts to handling escalated situations the AI cannot -- complex large-party negotiations, VIP calls, and guests with accessibility needs. Be the person in the restaurant who understands how to configure the AI system: set greetings, update specials, interpret analytics, and escalate issues to the vendor. That skill travels across every restaurant that adopts voice AI.

AI is sitting alongside you hereUpdate and act on guest profile data in the reservation platform: flag dietary restrictions and allergen notes when taking a reservation, check incoming VIP profiles before seating to brief the server, use SevenRooms AI Notes or equivalent to keep guest records clean and standardized, and add post-visit notes for guests who made special requests or lodged complaints so future visits are handled proactively.

Update and act on guest profile data in the reservation platform: flag dietary restrictions and allergen notes when taking a reservation, check incoming VIP profiles before seating to brief the server, use SevenRooms AI Notes or equivalent to keep guest records clean and standardized, and add post-visit notes for guests who made special requests or lodged complaints so future visits are handled proactively.[4],[5]

Tools picking this up
Where your edge is

Build a habit of adding one specific note per VIP reservation before the party arrives. A returning guest whose preferred seating is ready, whose name is used at the door, and whose anniversary the server already knows will leave a five-star review about "how they make you feel known." That outcome starts at the host stand, not the table.

AI is sitting alongside you hereManage the walk-in waitlist during peak service: accurately quote estimated wait times based on current turn rate (not optimistic guesses), add parties to the digital waitlist in the reservation platform, send SMS notifications when tables become available, and re-engage waiting guests to prevent silent walkouts.

Manage the walk-in waitlist during peak service: accurately quote estimated wait times based on current turn rate (not optimistic guesses), add parties to the digital waitlist in the reservation platform, send SMS notifications when tables become available, and re-engage waiting guests to prevent silent walkouts.[1],[5]

Where your edge is

Quote wait times conservatively and commit to a maximum, not a minimum. Guests who wait many minutes for a "20-minute wait" become hostile; guests who wait many minutes for a "30-minute wait" become grateful. A host who manages expectations accurately is the single biggest driver of positive lobby reviews.

Where restaurant hosts and hostesses go next

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

What each move takes

A direction you could grow

Food Service Managers

Experienced hosts who advance to floor supervisor and then develop operational breadth (scheduling, vendor management, P&L basics) are well-positioned for assistant general manager or food service manager roles. The host stand is the first place a restaurateur looks for GM potential: hosts who consistently run a calm lobby, de-escalate guests, and protect kitchen flow have already demonstrated the judgment that management requires. Median wages for food service managers are roughly double that of hosts, making this a meaningful income transition.

What you'd add
  • · Restaurant P&L literacy: food cost percentage, labor cost percentage, and how seating decisions affect table revenue per shift
  • · Inventory and ordering fundamentals: par levels, vendor relationships, waste tracking
  • · HR basics for hospitality: documentation, corrective action, scheduling compliance for tipped employees
  • · Reservation platform analytics: interpreting turn-time data, no-show rates, and cover-per-server metrics from OpenTable or SevenRooms to inform staffing decisions
What it takesSome new skills to pick up
Tools of the era

How has the work of restaurant hosts and hostesses changed since 1830?

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

  • Reservation ledger and headwaiter protocol (pre-telephone era)

    The first technology of the hosting function was the reservation book: a physical ledger maintained by the headwaiter or maitre d'hotel in which guest names, party sizes, and table assignments were recorded by hand. In American-plan hotels of the 1830s-1900s, where meals were included in lodging costs, the headwaiter managed a dining room that was more like a theater than a restaurant -- knowing which guests were regulars, which had status, and which required special accommodation. The ledger gave the dining room its institutional memory. Before the telephone, reservations were made in person the day prior or via written note delivered by messenger; the headwaiter's job was as much social choreography as information management.

  • Telephone reservation system (post-WWI, mass telephone adoption)

    By the 1920s, telephone adoption had reached mass market in American cities. For restaurant hosts and hotel dining rooms, the telephone transformed the reservation from an in-person or written transaction into a real-time voice interaction. The host stand now required a person who could manage both arriving guests and an inbound call queue simultaneously. Tea rooms of the Prohibition era (1920-1933) brought the hostess role to a new female-dominant format: the society hostess greeted and seated, answered the phone for reservations, and set the social tone of the establishment. The telephone added volume (more reservations per day) and coordination complexity (cancellations, last-minute changes) without reducing the in-person seating workload.

  • Chain restaurant standardization (scripted host stand, laminated seating chart)

    The chain restaurant explosion of the 1960s and 1970s -- Howard Johnson's, Denny's, Perkins, Friendly's, Shoney's, then Applebee's, TGI Fridays, Chili's, Olive Garden in the 1980s -- transformed the host role from an individual performance into a standardized protocol. Every chain location had the same host stand configuration, the same greeting script ("Welcome to Chili's, how many in your party?"), the same laminated seating chart rotated to show server sections, the same pager system for waitlisted parties (when applicable). The host was no longer a personality hire; the role was defined by the operations manual. This standardization made the position replicable at scale and drove wages toward minimum wage, since the job was now a procedure rather than a craft.

    Effect on the work

    Chain restaurant standardization dramatically expanded the total number of host and hostess positions in the US, growing the occupation from an estimated 90,000 in 1970 to approximately 310,000 by 2000. It simultaneously deskilled the role: the headwaiter who memorized hundreds of regulars' preferences was replaced by a teenage hostess following a laminated chart.

  • OpenTable and digital reservation platforms (1998 launch, 55,000 restaurants by 2024)

    OpenTable was founded on July 2, 1998 by Chuck Templeton, initially incorporated as easyeats.com, Inc., in San Francisco. Its core proposition was simple: move the reservation book from paper to software and make it accessible to diners online in real time. Until OpenTable, all reservations were taken by phone and recorded manually. For the host stand, OpenTable replaced the physical ledger with a software-managed guest list, added automated SMS reminders to confirmed reservations, and surfaced guest history (dietary notes, prior complaints, VIP status) at the point of seating. The platform grew to cover more than 55,000 restaurants globally by 2024. It did not eliminate the need for a human host -- the seating and greeting functions remained in-person -- but it shifted the cognitive load of reservation management from memory and paper to screen.

    Effect on the work

    OpenTable and similar platforms (Resy, Tock, SevenRooms) modestly reduced the administrative burden on host stands but did not reduce headcount directly. They raised the service quality floor (fewer double-bookings, better guest tracking) and created a new skill expectation: proficiency with reservation software became a baseline requirement for host employment from the mid-2000s onward.

  • Digital waitlist and SMS paging (Yelp Guest Manager, NoWait, Waitlist Me)

    The paper waitlist -- a handwritten list of names on a clipboard, with a host shouting names across a lobby -- was systematically replaced by digital waitlist platforms between 2010 and 2020. NoWait (founded 2010, acquired by Yelp 2017) and Yelp Guest Manager, along with Waitlist Me and similar tools, sent automated SMS messages when tables became available, eliminating the need for guests to physically remain at the entrance while waiting. For the host, this technology reduced lobby congestion and the awkward public announcement of wait times, but added a new responsibility: managing a software dashboard while simultaneously greeting arriving guests. The transition also introduced quote-accuracy accountability -- SMS timestamps now documented whether wait times were accurate or not.

  • AI-assisted reservation platforms (SevenRooms AI Notes, OpenTable AI table optimization)

    The generation of AI features embedded in reservation platforms arrived commercially between 2020 and 2024. SevenRooms launched AI Notes (automatic standardization and enrichment of guest CRM records), AI Feedback Summaries (weekly guest sentiment distillation from reviews), and AI-optimized table assignment suggestions. OpenTable integrated AI-powered waitlist time estimation and demand forecasting. These tools did not replace the host but changed the nature of the informational environment at the host stand: the host now works alongside a platform that surfaces actionable intelligence -- which arriving VIP has a known allergy, which server section is running slow, which guest historically requests a quiet corner. SevenRooms reported a reduction in time to respond to guest reviews at adopting restaurants.

  • Voice AI phone agents (Slang AI 2022, Yelp Host 2025, Hostie AI)

    Slang AI launched in 2022 and Yelp Host launched commercially in October 2025 at $149-$399/month per location. Both are voice AI systems that answer all inbound restaurant phone calls autonomously: taking and modifying reservations, quoting wait times, answering questions about hours and menus, and sending waitlist SMS links. Hostie AI, a competing platform, published case study data suggesting approximately 84% of routine incoming calls could be handled by the AI agent without human escalation. This is the first technology in the history of the role to directly automate a defined slice of what a host does -- not the in-person greeting and seating, but the phone-reservation intake that had been a core host responsibility since the 1920s. Restaurants using voice AI agents report freeing a sizeable share of host stand hours from phone handling during peak service periods.

    Effect on the work

    Voice AI phone agents represent the clearest current threat to host employment levels. If 84% of inbound calls are handled autonomously and phone calls account for a sizeable share of busy host time, the technology effectively reduces one host-equivalent of labor hours per shift at adopting locations. At scale, this could reduce the host-hours-per-cover ratio for full-service restaurants, contributing to the BLS-projected modest employment decline through 2034.

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Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop employment and pay by year

On record since1830
Latest US employment432,690 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$31,200 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+3.4% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 27 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
195045,000n/aEst., IPUMS USA Researched contextReport
197090,000$3,800Est., FRED (employment) Researched contextEst., US Department of Labor (pay) Researched contextReport
1990190,000n/aEst., FRED Researched contextReport
2000310,000$14,100Est., O*NET 30.3 (employment) Researched contextEst., US Department of Labor (pay) Researched contextReport
2003294,300$15,380BLS OEWS May 2003 Official statisticReport
2004316,400$15,630BLS OEWS May 2004 Official statisticReport
2005328,930$15,840BLS OEWS May 2005 Official statisticReport
2006340,390$16,170BLS OEWS May 2006 Official statisticReport
2007342,960$16,790BLS OEWS May 2007 Official statisticReport
2008349,990$17,510BLS OEWS May 2008 Official statisticReport
2009334,310$18,110BLS OEWS May 2009 Official statisticReport
2010329,020$18,450BLS OEWS May 2010 Official statisticReport
2011329,070$18,560BLS OEWS May 2011 Official statisticReport
2012341,400$18,580BLS OEWS May 2012 Official statisticReport
2013360,970$18,640BLS OEWS May 2013 Official statisticReport
2014372,670$18,720BLS OEWS May 2014 Official statisticReport
2015391,150$19,180BLS OEWS May 2015 Official statisticReport
2016404,360$19,980BLS OEWS May 2016 Official statisticReport
2017414,540$20,930BLS OEWS May 2017 Official statisticReport
2018416,950$22,160BLS OEWS May 2018 Official statisticReport
2019423,380$23,090BLS OEWS May 2019 Official statisticReport
2020316,700$23,880BLS OEWS May 2020 Official statisticReport
2021324,690$24,600BLS OEWS May 2021 Official statisticReport
2022400,420$27,720BLS OEWS May 2022 Official statisticReport
2023425,020$29,220BLS OEWS May 2023 Official statisticReport
2024427,150$30,380BLS OEWS May 2024 Official statisticReport
2025432,690$31,200BLS OEWS May 2025 Official statisticReport
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