How can hotels and restaurants handle guest complaints with AI?

Why complaint replies go wrong

Most complaints arrive by email, WhatsApp or a booking-platform message before they ever become a public review. The reply is usually written by whoever is on shift, late, under pressure, and without the service-recovery policy to hand. It ends up defensive, vague or over-generous: one manager offers nothing, another offers a free night. A complaint-reply Skill gives every shift the same starting point, built from your own policy, so the manager spends the time checking facts and deciding, not searching for the right words. It sits before the public review reply, and handling the complaint well often means that review is never written.

What the Skill drafts, and who decides

Swipe to read every column, or focus the table and use the arrow keys.

A worked example

Guest email: "Our room was not ready until 5:30pm although check-in is 3pm. We had a toddler with us and waited in the lobby with no update. Very disappointing start to our anniversary trip."
Checked facts: arrival 14:40, room released 17:25 after a late check-out was extended. No update given at 16:00.
Policy match: delayed room over 2 hours = apology + one listed gesture (manager's choice).

Dear Ms Rahman,

Thank you for telling us, and I am sorry. Your room should have been ready at 3pm, and you waited until after 5pm with a young child and no update from us. That is not the welcome we want for anyone, least of all on your anniversary.

The delay came from a late check-out in your room that we extended without planning for your arrival. We have changed how late check-outs are approved on busy days, and the front office will now update waiting guests every 30 minutes.

[Manager: choose one gesture from the policy list, e.g. dinner for two at the restaurant or a later check-out on departure]

If you would like to talk about it, please reply to me directly.

Kind regards,
[Name], Duty Manager

Front office · Room delay over 2 hours · Late check-out extended without arrival check · Action: approval rule for late check-outs on busy days · Owner: Front Office Manager · TO CONFIRM: gesture chosen

Synthetic guest, timings and policy for illustration only.

How it fits your operation

• Your policy, your gestures. The Skill offers only what your service-recovery matrix lists for that type of complaint. It leaves a placeholder rather than inventing a refund, discount or free night. When the policy changes, the GM approves the new version and the Skill is refreshed from it.
• The guest’s language. Replies can be drafted in the language the guest wrote in, with an English version beside it for the manager, as in multilingual guest messaging.
• Manual input is the default. Staff paste the complaint and checked facts into ChatGPT. Reading your inbox, booking platforms or PMS directly would need a separately agreed, configured and tested integration.

Guardrails

• Every reply is a draft. A manager checks it against what actually happened before it is sent. AI drafts can miss part of the complaint, state a cause the team has not confirmed or invent a detail, so the reply only uses facts the team has checked.
• Compensation is a human decision. The Skill suggests options from your policy; the manager chooses within their authority and the GM approves anything above it.
• Food safety, injury, security, discrimination and legal complaints are not handled by a draft. They go straight to the responsible manager and follow your incident procedure. ChatGPT does not monitor inboxes or raise alerts, and no instruction makes it do so.
• Start with past complaints with names, booking numbers and contact details removed. Real guest details belong in your approved ChatGPT workspace, configured with the access and retention your business decides. See ChatGPT governance.

A complaint-reply Skill can be a single Skill for AED 97. Hotels that want complaint replies, review replies and guest messages working together usually choose a fixed-price package from AED 3,500. See the pricing page.