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Examples

Artificial intelligence in hotels examples

Seven ways hotels use AI, from answering calls to scheduling staff. Each shows what the AI does and what the team still decides.

Updated 5 min read

The short answer

Artificial intelligence in hotels examples include answering calls and messages, handling bookings, preparing check-in, sorting guest requests, following up on reviews, scheduling staff and supporting pricing. Each takes repetitive work off the team so people can focus on guests.

Key points

  • Begin with the task that costs staff the most time
  • AI drafts and sorts; a person approves anything sensitive
  • Most examples run on the booking tools you already use

Examples

AI use cases in hospitality, task by task

No client results are claimed here: these are the tasks AI handles well, and where a person stays in charge.

  • Front desk

    Calls and messages answered at any hour

    An AI agent answers calls, texts and web chats about rates, amenities and directions, then passes complex requests to the desk with the context attached.

    Read the case →

  • Reservations

    Bookings captured and changed

    AI checks availability, confirms or changes a reservation and updates the booking system, so inquiries do not wait for someone to be free.

    Read the case →

  • Front desk

    Check-in prepared before arrival

    AI sends pre-arrival messages, collects ID and preferences, and flags special requests so the desk can greet guests faster.

  • Guest services

    Guest requests sorted and routed

    A guest asks for towels or a late checkout by text. AI classifies the request and sends it to housekeeping or maintenance.

    Read the case →

  • Marketing

    Review follow-up after the stay

    AI asks guests for feedback after checkout and drafts a reply to each review for a manager to edit and approve.

    Read the case →

  • Operations

    Staff schedules built around demand

    AI proposes shifts for housekeeping and the front desk based on bookings and past occupancy. A manager adjusts and confirms.

  • Revenue

    Pricing support from booking signals

    AI reads demand patterns, local events and competitor rates, then suggests price changes for a revenue manager to accept or reject.

    Read the case →

Why hotels look at AI now

  • Staffing gaps

    Most hotels report shortages.

  • Housekeeping

    The role with the most openings.

  • Front desk

    The second most-cited shortage.

  • Routine requests

    The work AI can take first.

Staffing is the pressure point. The American Hotel & Lodging Association survey found 65% of hotels still report shortages, and 71% have openings they cannot fill.

Housekeeping (38%) and the front desk (26%) are the roles hit hardest. Boston Consulting Group says AI can take on scheduling, inventory and routine guest requests so employees can focus on personal service.

Where adoption is heading

EHL's hospitality research forecasts AI spending in the sector growing more than tenfold between 2020 and 2031.

Its survey also found more than 80% of respondents expect AI to reshape pre-booking conversations and guest communications. Those two areas are where most AI use cases in hospitality begin.

AI use cases in hospitality industry settings

Good practice

  • Consent before outbound AI calls
  • Staff approve sensitive replies
  • Genuine guest reviews only

Avoid

  • AI-written fake reviews
  • Rewards for positive reviews
  • Outbound AI calls without consent

The examples above share one pattern: AI handles the repetitive step, a person keeps the decision. That split matters most in guest-facing work.

Two rules are worth knowing. Outbound AI voice calls need the guest's prior express consent, since the FCC places AI-generated voices under the TCPA.

The FTC's rule on fake reviews targets AI-generated reviews and bans rewarding people for reviews with a set sentiment.

  • Get consent before any outbound AI voice call
  • Do not post AI-written reviews as if guests wrote them
  • Do not offer incentives for positive reviews
  • Let a person approve sensitive replies

How to pick your first use case

  1. 01

    List repeating tasks

    Note what staff answer every day.

  2. 02

    Cost each one

    Hours times hourly cost.

  3. 03

    Pick the biggest

    Start where the cost is highest.

  4. 04

    Keep a person in charge

    Staff approve what matters.

Look at where staff repeat the same answer all day. Phones, booking changes and guest requests are the usual candidates, as on our hospitality page.

Our AI for hospitality work starts by mapping those repeating tasks and costing them in hours, so the first system targets the biggest saving. A broader view is in our AI use cases examples.

Our data

What AI answers when buyers ask

We asked ChatGPT, Gemini and Perplexity 10 buyer questions about AI for hotels and restaurants. They named 77 companies, and 73% appeared in only one of the three.

CriterionChatGPTGeminiPerplexity
Companies named273845
Sites cited mostcanarytechnologies.com (5 of 10)conduit.ai (4 of 10)roommaster.com and sendsquared.com (3 of 10)

Nexum measurement, October 20, 2026, via DataForSEO: 10 buyer questions to each AI, US English, 30 answers in total. 12 companies appeared in all three. Google showed an AI Overview for 9 of the 10 questions.

FAQ

Questions about AI in hotels

  • Hotels use AI to answer calls and messages, handle bookings, prepare check-in, route guest requests, follow up on reviews, schedule staff and support pricing decisions.

  • A small property can start with an AI that answers calls and texts about rates and availability, then sends booking confirmations. One process is enough to see whether the hours saved justify the next.

  • Guest communication and staffing tasks come first. With 65% of hotels reporting shortages, AI that handles routine requests and drafts schedules frees people for in-person service.

  • Not for the work guests value most. AI takes repetitive tasks such as routine answers and sorting requests, while staff handle exceptions, service recovery and personal attention.

  • For outbound calls, yes. Under FCC rules, that consent is needed unless an emergency or an exemption applies.

  • AI can draft replies for a manager to edit and approve. Fake reviews are a different matter: the FTC rule bans AI-generated reviews that pose as coming from real guests.

  • AI can suggest hotel rates from demand patterns, events and competitor prices. A revenue manager reviews each suggestion and keeps the final call.

Related

Keep reading

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