How hotels can use AI prompts? 20 Best Practices for Hotel AI Prompts

“An excellent model with a weak prompt can be outperformed by a weaker model with an excellent prompt.”

David Lamelas

Expanded Prompt Engineering Guide

A prompt is the instruction or question written to guide an AI model to give an answer, a result, an image, a video, that is, some output; it is the statement or instruction that tells the AI (NLP) what to do.

Think of the prompt as the request you make to a chef: if you say “I want food,” you get something generic; if you explain the dish, portions, dietary restrictions, and whether you like your steak well or rare, the result improves a lot. The same happens with AI.

For those technically curious: technically, the prompt is converted into tokens (text fragments) that the AI compares with patterns learned in its base training to predict the next sequence of words and build the response. Remember? LLMs (Large Language Models) or NLPs (Natural Language Processing), or more simply, the ChatGPT‑type models, are just AI models that build sentences very well, so well that they seem super intelligent and seem to know a lot, and they do (in the way I just described, building sentences, word by word, syllable by syllable).

What’s interesting: small changes in how a prompt is formulated, role, objective, limits, etc… (see more tips below), can drastically change the “reasoning” or style of the response. Like dialing a phone number: if you get one digit wrong, you call the wrong person. But in this case it’s even more frustrating, because often, with the same prompt you can get slightly different responses… As if dialing the same phone number called slightly different people. So it’s more complex than that, I’m sorry to say. That’s why it’s so important to be precise in prompt engineering, in the detail, in the fine tuning, and follow the best practices that I point out below, in order to minimize that natural randomness that NLPs (the ChatGPT‑type models) have, so that the answer is always more or less identical, and above all meets your request and the result is what you want.

So who is going to make the revolution of applied AI in hospitality?

In my opinion, it will be the smart hoteliers who master prompt engineering very well, because they are the ones who know which question is correct. Many just don’t yet know how to master it and take advantage of it with AI. Because part of the success of AI lies in the prompt, in the question you ask. Therefore, it is important to have hospitality‑industry specialists develop solutions for hospitality, because they are also those specialists who know how to ask the right question and give the right instructions without leaving any rabbit out of the hat.

Golden tip for beginners or the lazier:

By the way, golden tip: when you don’t know what quality prompt you should write, explain in simple words what you want to ChatGPT (or another LLM) and ask it to write the ideal prompt for you (also say which model you are going to use that prompt with).

Then use that prompt and that’s it. That is, take that prompt, copy to the model you want to use, make a few adjustments if you want, and you’re done, just wait for the result. It seems silly, but it works very well for those who are not yet very comfortable with prompt engineering or are at a more beginner level. But I don’t recommend this practice much, because that way you’ll never learn prompt engineering. But when hurry knocks at the door, it can also be a good solution, even for the more experienced.

✅ Best practices and what a good prompt should have and how it should be structured.

How can I create my prompt for the hospitality sector?

How to create my prompt for my hotel?

How hotels can use AI prompts?

1. Give a clear role

   - Say who the AI should “be” or which specialty it should follow: “Act as a prudent financial analyst,” “You are a 9th‑grade teacher,” “You are a B2B copywriter,” “Act as a lawyer,” etc…

   - If it makes sense, add seniority and sector.

   - For example, if you ask “Act as a lawyer,” the AI will seem like a real legal adviser.

   
   

2. Expose the problem

   - State the problem or situation, this helps give context.

   - It doesn’t need to be a novel though. Don’t tell the story of your life, be concise.

   
   

3. Clear objective and clear tasks

   - Explain what you want: a question, task, analysis, or ideas.

   - Declare the desired result in one sentence.

   - Example very simple: “I want a 150‑word summary for laypeople.”

   
   

4. Separate context from instructionsCreate sections. It works better like this:

   - Context: 2‑3 useful lines.

   - Task: what to do.

   - Restrictions: limits and policies.

   - Output: final format.

   
   

5. Give necessary details

   - Audience, level of knowledge, language (PT‑PT), tools, deadlines, word limits.

   
   

6. Use delimiters

   - Isolate content with code blocks, <tags> or “Text: …”. Avoid confusion.

   - Help the AI understand what is an instruction and what is a text you want to change.

   - For example: Translate the following text into English: “Sem prejuízo do disposto ….”.

   
   

7. Show what you want (and what you don’t want)

   - A good example is worth gold. It will help the AI understand your expectations about the expected result. Just like us humans, we always understand better when we are given an example.

   - For example write: Here’s an example of the type of response to give to a customer in a complaint: “Dear Mr. Tiago Gonçalves, Thank you very much for bringing this point to our attention ….”

   - Bring also a short anti‑example to exclude undesired results (for those who already know the quirks of some AI models, know how important it is to give anti‑examples).

   
   

8. Restrictions and limits

   - It is very important to say what you do not want!

   - After some time we already know the tricks of a given model, and then we know we must say to avoid those tricks.

   - For example: “Never use em‑dashes —”. By the way, another tip, if you don’t want it to be obvious you used AI, don’t use “—”, because that “—” gives away that you used AI, since that “—” was never used until ChatGPT appeared. Actually I challenge you to try to find on your keyboard that key to type that em‑dash “—”. Understood now?

   - Declare costs, reading time you have, applicable policies and requirements for privacy (anonymization of sensitive data).

   
   

9. Format and length

   - Say if you want a list, table, bar chart, steps, JSON… say how you want it.

   - Indicate counts.

   - For example: “Give 10 different suggestions”, “A list with max. 6 bullet points”.

   
   

10. Ask for reliable references

    - On factual topics, ask for sources and links.

    - Ask for links to news so you can validate facts.

    
    

11. Reduce hallucinations

    - Another golden tip, to lessen hallucinations use this tip below.

    - If the AI does not have a basis to prove those facts, ask it to say “I don’t know / low confidence”. Include in all prompts something like:

“If you are not 100% sure about an answer or a fact say you don’t know or that the confidence level is low; don’t worry about appearing less certain, it’s normal not to know everything; feel free with me, tell me when there is something you don’t know. The worst you can do is invent something just because you are not 100% sure.”AI models work via probabilities so they understand this part “If you are not 100% sure about an answer or fact say you don’t know or that the confidence level is low…”.

12. Demand justification, but no essays

    - Ask for criteria and determining factors in short points (avoid long reasoning when you only care about the result).

    - Ask for criteria and factors in bullet points. Short and direct.

    
    

13. The more complete the prompt, the better the result

    - A bit more precision now saves a lot of rework later.

    
    

14. Address gaps head‑on

    - Allow the AI to ask for clarification if something critical is missing.

    - If you proceed with assumptions, have them listed.

    - Authorize a request for clarification when essential data is missing or, alternatively, explicit assumptions.

    - For example include: “If my prompt is not clear, ask for the clarifications you need in order to give a 100% correct and assertive response.”

    
    

15. Ask for creative variety

    - If you want a rich response with several perspectives or styles, ask; be demanding.

    - Ask for several responses and put them in competition.

    - 3 distinct options (e.g., low/medium/high effort) → a synthesis or final conclusion.

    
    

16. Give enough context, not a novel

    - Cut what is superfluous. Summarize long attachments in points.

    - Sometimes if you include something not that essential, it can confuse the AI; it may focus too much on that part which you put and wasn’t essential.

    - Here, as in everything, sometimes less is more.

    - Detail makes all the difference, but neither extreme.

    
    

17. For code and data

    - Specify language/version, environment, I/O, test cases and expectations of complexity.

    
    

18. Preserve format when localizing

    - In translations/summaries, ask to keep formatting, emojis, line breaks, tags.

    
    

19. Output evaluation

    - Request a score (0–10) against criteria and suggestions for improvement of the output or prompt itself.

    - Always leave space for the AI to be self‑critical of itself or whatever it is.

    
    

20. Test → measure → refine; if necessary restart from scratch

    - Do A/B of prompts. Compare against acceptance criteria. Adjust and repeat.

    - Sometimes you don’t hit the right prompt at first. In that case, sometimes the best is to understand what failed and restart, putting that learning about what failed in the next prompt and try again.

    - Sometimes it drives you crazy, trying to correct a result via iteration (adjusting and tweaking the result given by an AI through conversation/prompts), because no matter how you explain, the AI may not understand. For example many times text you request to be in an image ends up off‑lines or misaligned, so sometimes it is harder to correct that mistake than to restart the conversation and include that detail from the start (“capable of fitting the text inside the image”, “if necessary reduce font size of the text so it fits in the image”).

🧪Very simple template ready to paste

I know it’s not always possible to follow all best practices in day‑to‑day. So here is the bare basics, just adapt.

Role: Act as an academic synthesizer.

Explain problem & objective: Expose {problem}. Explain {theme} for {audience}.

Context: {2‑3 sentences} or {a table}

Task: Produce a summary in 5 points.

Restrictions: Max. 180 words; PT‑PT; without jargon.

Sources: Cite 2‑3 reliable sources.

Output: Markdown with title, list and section “Limitations”.

✔️ Quick checklist before sending the prompt. How hotels can use AI prompts?

• Assign a role to the GPT

• Tone, language, align with audience

• Define clear objectives (command, question, instruction)

• Split your request (e.g., separate instruction from context)

• Include essential details, be descriptive

• Use delimiters (e.g., “text”)

• Expectations, show examples or what you don’t want

• Define response length or format

• Reference reliable texts

• Eliminate hallucinations; if not ≥100% probable, say “I don’t know”

• Request or show Reasoning “step by step”

• The more complete the prompt, the better the result

Test, Test, Test (experiment > results > refine) and often it’s best to start over with the learning you got, if the first result wasn’t satisfactory.

❓ Frequently Asked Questions (FAQs)

1. What is a prompt in AI and why does it matter for hotels? A prompt is the instruction or question you give to an AI model to generate a response. In hotels, better prompts mean more accurate guest communication, improved marketing content, and smarter automation.

2. How can AI prompts improve guest experience in hotels? AI prompts can personalize guest communication, answer questions faster, provide tailored recommendations, and create a smoother booking or check-in experience.

3. Why is prompt engineering important for hospitality? Because asking the right question leads to better results. Hoteliers who master prompt engineering can make AI tools more efficient and aligned with real guest needs.

4. Can AI prompts help reduce hotel staff workload? Yes. With well-structured prompts, AI can handle repetitive tasks like FAQs, booking confirmations, upselling offers, and guest feedback, freeing staff to focus on human interaction.

5. What are some examples of AI use cases in hotels? Chatbots for guest support, upselling through personalized offers, automated review replies, multilingual translation for international guests, and AI-driven market analysis.

6. What makes a “good” AI prompt for hotels? A good prompt is clear, structured, includes context (e.g., guest profile, preferences), defines the expected format, and avoids ambiguity.

7. How can hotels avoid AI “hallucinations” or wrong answers? Hotels should instruct AI to say “I don’t know” when uncertain, set strict guidelines in prompts, and always ask for sources or low-confidence warnings.

8. Do hoteliers need technical skills to use AI prompts effectively? No. While technical knowledge helps, most hotel professionals can learn prompt best practices through examples and structured templates.

9. What are the main benefits of using AI prompts in hotel marketing? Faster content creation, consistent brand tone, personalized campaigns, and better SEO-friendly text for websites and social media.

10. What’s a quick template hotels can use to start with AI prompts? Define the role (e.g., “Act as a hotel concierge”), provide context (guest request, language, preferences), state the task (summarize, reply, suggest), add restrictions (word count, tone), and request clear output (list, email, script).