The 3 Pillars of During-Stay AI: How To Operationalize AI Strategy

This blog explores the three pillars of during-stay AI in hospitality, integration, goal setting, and guest adoption, and  how hotels can move from pilots to real operational impact.

AI is no longer a future topic in hospitality. Most hotel chains are already using it in some form, and many are planning to expand their investments. Yet when we look closely at where AI actually delivers value today, a clear pattern emerges: most initiatives stop before the guest checks in.

During the stay, when guest expectations are highest and operational pressure peaks, AI is still used cautiously. This is not because hotels resist AI, or because guests are not ready. Research shows the opposite. The real challenge lies in execution.

Based on insights from the h2c’s AI & Automation Study and broader guest research, one conclusion stands out: hotels can unlock significant value during the stay by applying a focused 80/20 approach and building on three practical pillars.

Because the reality is: AI is wanted, but without a solid execution, the projects may never go beyond pilots.

Why During‑Stay AI Matters

A large share of in‑stay guest requests is predictable. Questions about Wi‑Fi, breakfast times, housekeeping, or hotel services come up every day, in every property. These interactions are important, but they are rarely complex.

Handled manually, they consume staff time and attention, especially during peak periods. Handled digitally, they can be resolved faster, more consistently, and with less effort.

This is where the 80/20 logic applies. Roughly 80% of guest requests can be handled with a relatively small amount of automation. That is, of course, if the right foundations are in place. The goal is not to automate everything, but to remove friction where it makes sense and protect the moments that require a human touch.

To make this work in practice, three pillars are essential.

Pillar 1: Integration

Not every guest interaction should be automated. Clear goals are essential to avoid over‑automation and protect service quality.

A practical way to define these goals is to separate efficiency use cases from experience use cases.

Efficiency use cases include high‑frequency, factual requests where speed and accuracy matter most. Guests do not expect empathy when asking for Wi‑Fi details or towel delivery. They expect fast answers.

Experience use cases are different. Service recovery, personal recommendations, or proactive gestures require judgment and empathy. These moments should remain human.

AI’s role is not to replace these interactions, but to support them by providing context and freeing up staff time.

Pillar 2: Goal Setting

The business traveler arrives with a mindset closer to the family than the couple, but with far less flexibility. Often arriving late, their focus is efficiency, not exploration. Once in the room, priorities are clear: confirm Wi-Fi access, check breakfast times, and prepare for the next day.

Like families, business travelers want clarity and control. Unlike couples, they have little tolerance for interruptions. Their stay follows a tight routine, early mornings, short evenings, and minimal interaction.

What business travelers expect is speed and predictability. AI-supported guest journeys help by filtering information and options to what’s relevant at each stage of the stay. For hotels, this reduces routine inquiries and keeps interactions efficient, without compromising service quality.

Pillar 3: Guest Adoption

Even the best‑integrated AI will fail if guests do not use the digital channels behind it.

Guest adoption is therefore not a secondary consideration. It is a prerequisite for ROI.

Hotels need to ensure that digital touchpoints are visible, intuitive, and part of the natural guest journey. Solutions that guests already engage with during the stay create far more value than tools that require extra steps or downloads.

As a benchmark, hotels should aim for at least half of in‑house guests using a digital channel during their stay. Below this level, automation remains a side project instead of a real operational lever.

From Pilots to Practice

The hesitation around during‑stay AI is not rooted in guest resistance or lack of ambition. It comes from fragmented systems, unclear goals, and digital tools that never reach critical mass.

When integration, goal setting, and guest adoption come together, AI becomes an enabler rather than a risk. It reduces operational friction, improves response times, and creates space for more personal service.

During‑stay AI is not about adding more technology to the guest journey. It is about applying AI where it matters most to handle the predictable efficiently and give people more time for what makes hospitality human.

This article is based on insights from the whitepaper “AI in Hospitality: Why the Real Opportunity Lies During the Stay”, drawing on the h2c AI & Automation Study and guest research across the industry.

_{Published on 17 February 2026}