By Lance Thompson, president of VIVI - 3.25.2026
Most hotel operators rely on standard methods to understand guests, such as surveys, comment cards, online reviews, and conversations at the front desk or in the lobby. These inputs matter, but if we are honest, they only tell us part of the story.
Guest surveys capture a small percentage of the people who actually stay with us. The people who respond are usually either extremely happy or extremely frustrated. The middle majority rarely fills them out. That means operators spend a lot of time making decisions based on a thin slice of feedback. AI is allowing something different to emerge.
Most operators initially think about AI in a very practical way. Can it answer the phone 24 hours a day? Can it help guests quickly find information? Can it reduce pressure on the front desk when everyone calls at the same time? All of this is valuable, but what is surprising is the data that comes with it.
When an AI system answers calls, texts, and chats, every interaction is captured. Every question. Every request. Every moment where a guest needed something. The volume of insight becomes dramatically higher than what any survey program can deliver. And it starts to reveal patterns.
When Guests Actually Reach Out
One of the first things you see is timing. When are guests actually reaching out for help? What time of day are the calls coming in? When do questions spike? AI data may show a very clear pattern, which is that a large percentage of guest questions happen outside of the moments when hotels traditionally expect them.
Late evening calls about dining options. Guests asking about spa hours after dinner. Transportation questions late at night before an early flight. Activity planning happening after guests return from the day. When operators can see those patterns clearly, staffing decisions get smarter. Information can be delivered earlier. Some problems disappear entirely. It is operational insight that rarely shows up in a survey.
Anticipating What Guests Expect to Find in the Room
Another interesting signal comes from what guests ask for after they arrive. Extra blankets. More coffee pods. Phone chargers. Humidifiers. Yoga mats. Water kettles. Any operator will recognize these requests. They happen every day. But when you aggregate them across thousands of interactions, you start to see something different. Guests are telling you what they expected to already be in the room.
That is incredibly useful feedback. If 50 guests ask for the same item in a month, that is no longer a random request. It is a design signal. Often the solution is simple. Adjust the standard room setup and eliminate hundreds of service calls at the same time.
Which Amenities Generate the Most Questions
AI interactions also show operators where information is missing on websites, apps, or collateral. Guests ask about the fitness center. Pool hours. Spa availability. Shuttle schedules. Equipment rentals. Activity reservations.
When the same questions appear over and over again, it is usually not because guests are being difficult. It is because the information is harder to find than we think. Sometimes it is buried on a website. Sometimes the pre-arrival email did not highlight it. Sometimes, signage on property is not doing its job. Instead of guessing, operators and marketers can see exactly where guests are getting stuck throughout their experience.
Maintenance Signals That Used to Be Invisible
One of the most practical insights comes from maintenance-related interactions. Guests mention things that are slightly off. The air conditioning is not cooling properly. Water pressure feels weak. A patio door sticks. A light flickers. The television remote does not respond. Normally, these get handled as individual work orders. Engineering fixes the issue and moves on.
But when AI logs every interaction, patterns start to appear. Maybe 20 different guests mention water pressure over a few months. Maybe several rooms report the same HVAC problem during the same time of year. Maybe a particular building generates repeated calls about door locks or sliding glass doors. This kind of pattern is incredibly valuable for engineering teams and ownership groups.
Instead of waiting for equipment to fail or relying only on scheduled replacement cycles, operators can see early signals coming directly from the guest experience. It becomes another input into capital planning decisions.
If a system is quietly generating guest complaints across multiple rooms, it is often smarter to address it proactively than to wait for it to escalate into negative reviews. In other words, guests are helping operators prioritize capital investment without realizing it.
Language Trends and Who Your Guests Actually Are
Another interesting data point comes from language detection. Many hotels and resorts serve international travelers, but operators often underestimate how many languages are actually being spoken by their guests. AI interactions surface this quickly. If Spanish conversations suddenly increase. If Portuguese or Mandarin begins appearing regularly. If certain languages spike during particular seasons.
That information helps operators adjust staffing, concierge resources, and digital content. It also gives a clearer picture of where guests are coming from to inform marketing efforts. Historically, this kind of analysis took months to piece together.
What Guests Are Really Ordering
In-room dining interactions also produce useful insights. When guests place orders through AI, the system captures the modifiers. Extra sauce. Gluten-free substitutions. Dairy alternatives. Added protein. Portion changes. Over time, these details become patterns.
Operators can see which menu items generate the most customization and which dietary preferences appear most frequently. That can inform menu design, purchasing, and even new upsell opportunities. It is a level of detail that rarely shows up in traditional POS reporting.
Reading the Emotions of the Guest Experience
One of the more interesting developments is sentiment analysis. AI systems can evaluate the tone of guest messages and calls. Not just what the guest asked for, but how they asked. Are they frustrated? Curious? Urgent? Excited? When those signals are aggregated, operators can see where emotional friction exists in the guest journey.
If confusion repeatedly shows up around transportation or reservations, there is probably a process issue. If frustration spikes around a particular amenity, something is not working as intended. Instead of waiting for a negative online review, operators can see the signal much earlier.
A Different Kind of Feedback Loop
Hospitality has always valued guest feedback. But for decades, the industry relied on tools that captured only a small percentage of guest voices. AI has the chance to change that.
When every guest interaction becomes a data point, operators gain a much clearer understanding of what guests actually experience during their stay. Not what they remember days later when filling out a survey, but what they needed in the moment. The initial goal may simply be answering the phone 24 hours a day, but the real value is the insight that comes with it.
With 25 years in luxury hospitality operations and less than one year of experience building AI systems for these same hospitality operations, one thing has become very clear to me: the hotels that learn from this data will not just respond to guests better, they will start designing better experiences before the guest ever needs to ask.
Lance Thompson is president of VIVI, a centralized, no-code AI platform designed specifically for the hospitality industry to automate guest services, internal workflows, and communication. Developed by experts in AI and hospitality, it functions as a “digital employee” that handles tasks such as reservations, concierge services, and staff support. He is a longtime hospitality executive with experience spanning hotel operations and enterprise AI strategy. Drawing from leadership roles in both hotel management and applied AI, he advises hospitality organizations on implementing intelligent systems that enhance service delivery while aligning with operational, technical, and security requirements.
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