Lede
The horizon of AI in travel, tourism and hospitality is no longer just about concierge chatbots and fancy room features—it’s now proving central to sustainability, guest trust, and technology acceptance. Recent studies from China to Europe show that robotic services, energy-saving practices, and guest perceptions of smart rooms are yielding measurable impacts. This post dives into fresh developments, real case studies, and what operators must prioritise.
TL;DR
- Chinese Gen Z guests rank assurance, entertainment, anthropomorphism and physical tangibles highly when evaluating hotel robots; reliability was *not* a strong predictor of reuse. (frontiersin.org)
- 56% of hotels feel pressure to upgrade tech; but many guests struggle with usability of smart room features like lighting, climate or entertainment controls. (ftnnews.com)
- Sustainability gains: Iberostar used AI (via Winnow) to reduce food waste by 1,100+ tonnes in 2023 and is also optimising hotel energy systems with predictive environmental data. (reuters.com)
- National Tourism Organisations (NTOs) across Europe are increasingly using AI (especially in marketing and content generation) but many are still at pilot stage; challenges around training, capacity, and strategy persist. (etc-corporate.org)
- A new recommendation framework “Collab-REC” helps balance recommendations between popularity, user preference, and sustainability, showing improvement in surfacing lesser-visited locales. (arxiv.org)
Sustainability at Work: From Waste Reduction to Emissions
One of the strongest recent examples is Iberostar’s collaboration with Winnow, where AI-enabled tracking of food waste (with smart bins and cameras) allowed the hotel chain to reduce waste by over 1,100 tonnes in 2023. On top of that, Iberostar is using predictive models to adjust its energy use—such as air conditioning and electricity systems—based on weather forecasts and usage patterns. (reuters.com)
In aviation, American Airlines and Google’s Project Contrails is using AI to avoid contrail-forming airspace, which helps reduce aviation’s environmental impact significantly (contrails trap heat etc.). (reuters.com)
Guest Experience & Robot Service Quality
A study among Generation Z in China (400 respondents familiar with robotic delivery in hotels) evaluated service robots across five dimensions: reliability; assurance; entertainment; anthropomorphism; and tangibles. The findings showed that assurance, entertainment, anthropomorphism and tangibles significantly influence whether guests want to continue using robots. Surprisingly, reliability (how dependable the robot is) did *not* show a statistically significant effect. Personal innovativeness (how willing someone is to try new tech) moderates many of these effects. (frontiersin.org)
Smart Rooms: Innovation vs Usability
Hotels.com’s 2025 Hotel Room Innsights survey (450+ hotels globally) reveals many properties are investing more in comfort-enhancing tech (“ComfortTech”) like smart lighting, smart speakers, high-speed WiFi than full robot or automation systems. But there’s a gap—guests report confusion around using room tech features. In response, over half of hotels now provide verbal walkthroughs at check-in to explain how systems work (lighting, entertainment, AC etc.). (ftnnews.com)
National Tourism Organisations: Adoption & Barriers
The European Travel Commission’s recent mapping study shows that NTOs across Europe are using AI actively, especially in marketing (content generation, sentiment analysis, translation). However, many are still running pilots rather than embedding AI operationally. Barriers include limited AI expertise, lack of clear roadmaps, budget constraints, and uneven capacity among organisations. (etc-corporate.org)
Recommender Systems: Aligning Popularity, Preference & Sustainability
A recent academic framework, Collab-REC, implements a multi-agent system to balance popularity bias in city recommendations with sustainability and user preference. It combines agents focusing on personalisation, sustainability, and popularity, then merges outputs in a moderated way. Results from European city-query experiments show this produces more diverse recommendations (less obvious, over-touristed spots) while maintaining relevance. (arxiv.org)
Case Study: Hotels Robots & Long-Term Use
As noted above, the study of Gen Z’s responses to robotic services shows that perceived fun, design, and human-like qualities often matter more than technical reliability. Robots that look friendly, act in an engaging way, and offer tangible value (good physical design, easy interface) are more likely to be reused. (frontiersin.org)
Case Study: Tech-Up in Smart Rooms & Guest Frustration
From the Hotels.com Innsights survey: many hotels are installing fancy tech around rooms, robots, AI concierges etc. But guests struggle with basic tasks. Over 50% of hotels now offer verbal tech walkthroughs; 70% report guests still prefer human contact for key service touchpoints. This suggests that technology must be intuitive. (ftnnews.com)
Case Study: Collab-REC & Sustainable Destinations Surfaced
Using the Collab-REC framework, researchers found that balancing popularity, sustainability, and preference can bring forward lesser-known destinations in recommendation outputs—helping mitigate overtourism. This shows that AI recommendation systems can be designed to better serve both travellers’ interests and destination sustainability. (arxiv.org)
FAQ
- Can robot reliability be ignored when guests decide whether to reuse services?
No; it isn’t ignored entirely, but recent research found that assurance, entertainment, anthropomorphism and tangible design features had more influence on continuance intention than reliability among Gen Z in China. (frontiersin.org) - Do guests prefer human interaction over technology?
Yes, especially for tasks considered important: check-in, problem resolution, and initial orientation. Hotels.com survey shows 70% of hotels report guests still prefer speaking with staff in such moments. (hotelmanagement.net) - Is AI actually reducing environmental impact in tourism?
Yes; for example, AI-based food-waste tracking saved over 1,100 tonnes in one hotel chain; flight route optimisation (Project Contrails) cuts contrail formation which traps heat. (reuters.com) - Are recommendation systems biased toward popular destinations?
Often they are; but new systems like Collab-REC are showing ways to balance popularity with sustainability and user preferences. (arxiv.org) - What is personal innovativeness?
A trait reflecting how willing someone is to try new technology early. In the robot service study, it influenced how strongly guests responded to attributes like entertainment or anthropomorphism. (frontiersin.org) - How can hotels reduce guest confusion with smart room tech?
By providing walkthroughs at check-in, simplifying user interfaces, offering help documentation or staff support, and prioritising intuitive design. (ftnnews.com) - Does using AI in tourism require lots of investment?
Yes; while there are cost savings (waste reduction, energy savings), implementing robotics, training staff, integrating systems, etc., can be expensive. But many operators report ROI when tools are well-designed. (reuters.com) - What role do national tourism organisations play?
They are often early adopters or coordinators. They test tools for marketing, content generation, translation, but many are still at pilot stage or limited by capacity. (etc-corporate.org) - Are AI-powered recommendations trustworthy?
Can be—especially when systems like Collab-REC are used to include sustainability and user preferences and avoid over-promoted popular destinations. Transparency about data sources helps. (arxiv.org) - What must businesses do to succeed with these trends?
Focus on user experience (intuitive tech), sustainability, staff training, ethical deployment, balancing novelty with reliability, listening to guests’ feedback, and selecting tools that align with both guest needs and operational ability.
Mini-Glossary
| Term | Definition |
|---|---|
| Assurance | A dimension of service quality relating to users’ trust in competence, courtesy, and security provided by a service or robot. |
| Anthropomorphism | Attributing human-like traits (appearance, behaviour) to non-human agents (robots or AI avatars). |
| Entertainment (in service robots) | The fun or enjoyable aspect provided by robot features, interactive design, or novel functionality. |
| Tangibles | The physical or sensory attributes such as appearance, interface design, or decor that affect guest perception. |
| Reliability | The ability of a system to perform consistently and correctly over time. |
| Personal Innovativeness | A person’s tendency to try new technologies early; influences technology adoption. |
| Recommendation System | An algorithm or service that suggests travel destinations, hotels, activities based on data and preferences. |
| Sustainability Filter | A constraint in recommendations that considers environmental or social impact, e.g., eco-friendly lodging, carbon emissions etc. |
| ComfortTech | Smart room technologies aimed at user comfort, like lighting, climate controls, smart TVs, etc. |
| Overtourism | Excessive tourism in particular places causing environmental, social, or infrastructure strain. |
| User-Centred Design | Design approach that emphasises usability, intuitive interaction and guest feedback rather than novelty. |
| Robotic Delivery | The use of robots for delivering items (amenities, food, etc.) within hotel properties. |
| Meta-UTAUT | A model combining Unified Theory of Acceptance and Use of Technology with added factors like trust, aesthetics and interaction. |
Conclusion & Takeaway
The travel & hospitality industry stands at a tipping point: AI is delivering tangible sustainability wins, guest satisfaction evolves around trust, design, and novelty, and smart rooms are only useful if guests can use them. For operators, success depends on balancing innovation with usability, investing in intuitive design and training, and embedding sustainability into every decision.
Infographic Design Brief
- Title: Key Trends: AI, Guest Acceptance & Sustainability in Hospitality 2025
- Sections:
- Robot Service Quality Attributes (Assurance, Entertainment, Anthropomorphism, Tangibles)
- Smart Rooms & Guest Confusion Stats (percentages of hotels, features)
- Sustainability Gains (food waste saved, energy reduction examples)
- Recommender Systems – balancing popularity & sustainability (Collab-REC insight)
- Colour Palette: AgenticTourism.ai brand colours – deep purple, lavender, white, black (for text)
- Style: Clean icons, simple bar/pie charts, minimal text, emphasis on clarity
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