Friday evening, 10:15 p.m. A family from Munich sends an email asking whether a room with a mountain view is still available, whether their dog is welcome, and whether a late check-out would be possible. The front desk has long since closed for the night. The enquiry sits unanswered until Monday morning – and by then the family has already booked somewhere else.
This happens every day in hospitality and hotel businesses across the Alpine foothills. According to Acquaint Soft (2026), AI in production can automate 40–65% of guest interactions and reduce front desk workload by 20–35% within just a few weeks of deployment. These are not promises from Silicon Valley – they are figures that are equally realistic for a guesthouse in Bad Tölz or a family hotel in Miesbach.
Without AI: The receptionist answers 30–60 emails every day, at least half of which are identical questions about check-in times, parking options, or cancellation policies. Guest feedback from Google, Booking.com, and TripAdvisor gets skimmed – if at all – once a week. Upselling (wellness packages, breakfast in bed, excursion tips with a booking link) happens by chance and depends on whether the team member has the time and energy in that moment.
With AI: An AI chatbot on the hotel website and in the email inbox answers standard enquiries around the clock – in German, English, and Italian. Guest feedback is automatically evaluated, categorised, and prioritised. Upselling offers are delivered in a personalised way based on booking data: someone who books with a dog automatically receives a tip about the dog-friendly hiking trail with a mountain hut – including a reservation link.
According to askHermis (2026), 90% of hotels have already introduced AI-powered guest communication or are planning to do so. Those who wait any longer are not just losing time – they are losing guests to competitors who are already responding.
1. Automating Booking Communication
The first bottleneck is almost always the email inbox. In 7 out of 10 of our hospitality projects, manually answering standard enquiries was the first bottleneck we tackled together – this is a clear observation Softstorm has made from practical work in the Alpine foothills.
Here we rely on n8n as our automation platform. Compared to Zapier or Make, n8n is significantly more flexible for complex workflows – for example, when an enquiry first needs to be checked against an availability API, then assessed by a language model, and finally sent out as a personalised reply. This can be self-hosted with n8n without expensive pro licences, which is a real advantage for privacy-conscious businesses in Bavaria.
As the underlying language model, we frequently use the Claude API from Anthropic. Claude is particularly strong at writing friendly, natural-sounding text – important when the reply should not read like an auto-responder from 2012. Claude also follows specified guidelines precisely, which is helpful when formulating cancellation policies or house rules.
2. Automatically Evaluating and Prioritising Guest Feedback
A real-world example: a guesthouse in Wolfratshausen, through an AI-powered feedback evaluation system, identified for the first time that guests had been complaining about the Wi-Fi signal in the top-floor rooms for months – across different platforms, in different languages. Without AI, this pattern had been lost in the noise. After the fix (a mesh router, installed in an hour), the Google rating rose by 0.4 points.
There is nothing magical about this. It is consistent data analysis that a small property simply could not manage before – because the capacity was not there.
Our AI agents handle the retrieval, classification, and summarisation of reviews from multiple platforms. The result lands in the owner's inbox every Monday morning as a short summary – with the three most important topics of the week.
3. Delivering Upselling in an Automated and Personalised Way
Upselling sounds like something for large hotel chains. But it is not. Even a guesthouse with 12 rooms can automatically offer a breakfast basket for the balcony – when someone books a room with a balcony. Or offer a sauna voucher when a guest is staying for two nights.
These personalised triggers can be implemented with n8n and a simple CRM dataset. The effect: according to Canary Technologies (2026), 82% of hoteliers expect AI use in their organisation to increase – precisely because they recognise these small revenue levers in their day-to-day operations.
If you want to think bigger, you can bring in an AI agent that proactively creates offers based on booking patterns – similar to what we have already implemented for other service providers in the region.
Here is the honest caveat we share in every project: AI chatbots hit clear limits as soon as enquiries become emotionally sensitive or legally relevant. If a guest wants to cancel a wedding, reports an accident on the premises, or describes a special situation such as an allergy with a medical background – a person must take over.
This is not a flaw in the system. It is by design. Good AI automation recognises these situations and hands them off cleanly to the front desk – with all the context gathered so far, so nobody has to repeat themselves.
And here is our strongly held view, one we have arrived at through many conversations with hoteliers in the Alpine foothills: Most providers sell hotels an all-inclusive carefree package that is, in reality, an all-inclusive overwhelm package. What small properties need are two or three cleanly functioning automations – not an AI strategy for 2030.
If you want to know what this could look like concretely for your hotel or guesthouse, we do not recommend a workshop or a whitepaper – we recommend a 30-minute conversation.
We analyze your processes, identify automation potential and show you which digital systems really make sense.
