AI Hospitality Alliance
Back to Research
Academic ResearchFebruary 23, 2026International Journal of Interactive Mobile Technologies (iJIM), Vol. 20 No. 7

AI-Powered Mobile Applications in Hotels: Guest Personalization, Operational Efficiency, and Sustainability

Qualitative systematic literature review of how AI-powered mobile apps reshape luxury hotels across three outcomes: guest personalization, operational efficiency, and sustainability. Finds that AI-mobile capabilities (pre-arrival personalization, mobile check-in, digital keys, smart-room controls, chatbots, loyalty integration) deliver standardized service, faster response times, lower staffing pressure, and 20–30% energy savings via AI thermostats — but only when paired with employee training, change management, transparent data practices, and a hybrid model that keeps humans on high-touch moments.

Authors

Amila Ishanthi H. M., Neetu Jain, Manpreet Kaur

Article content

What the paper studied

A qualitative systematic literature review (SLR) with thematic synthesis of academic journals, industry publications, and hotel case studies from the last five years. The authors examined how AI-enabled mobile apps in hotels — particularly luxury properties — contribute to three outcomes: guest personalization, operational efficiency, and sustainability. The global AI-in-hospitality market was valued at USD 15.69B in 2024 and is projected to reach USD 58.29B by 2029 (≈30% CAGR), framing the urgency.

Key findings

  • **Three convergent outcome areas.** Across the literature, AI-mobile apps consistently deliver (1) frictionless guest experiences, (2) operational efficiency gains, and (3) sustainability improvements.
  • **Standard feature set.** AI-mobile capabilities cluster around: pre-arrival personalization, mobile check-in/out, digital room keys, smart-room controls (lights, temperature, entertainment), in-app service requests and payments, loyalty program integration, and AI chatbots/virtual assistants.
  • **Chatbots handle the bulk of routine load.** Between 60–70% of standard guest questions can be fielded by AI-enabled chatbots, easing front-desk and concierge demand and enabling 24/7 service.
  • **Multilingual AI reduces misunderstandings.** AI-powered language translation in mobile apps drives higher satisfaction for international-facing brands.
  • **Measurable energy savings.** One hotel chain reported **20–30% HVAC energy cost reductions** after implementing AI thermostats that adjust based on occupancy and time of day.
  • **The personalization paradox.** Guests want personalization but are wary of data collection. Trust depends on (a) brand reputation, (b) transparent data communication, and (c) giving guests visible control over their data.
  • **Hybrid service models win in luxury.** AI should automate routine and back-office tasks; humans should own high-touch moments, emotional connection, and service recovery. Fully automated luxury service can feel cheap.
  • **Implementation, not technology, is the bottleneck.** Failures correlate with poor employee training, weak change management, and insufficient pilot/testing — not with the AI itself. Successful rollouts share: phased pilots, vendor partnerships, employee education, and gradual deployment.
  • **Sustainability becomes a profit center, not a cost.** Paperless workflows, AI-driven HVAC, predictive monitoring, and digitized guest transactions reduce energy, water, and paper consumption without hurting margins.

Why it matters for hospitality

Luxury hotels are losing physical-asset differentiation as rooms, amenities, and locations commoditize. Digital-enabled personalization through AI mobile apps is one of the few remaining long-term moats. This paper makes a clean case to operators that mobile + AI is not an experimental side project — it is a strategic competitive lever, with documented financial, experiential, and environmental upside. It also names the failure modes most luxury hotels actually hit (staff resistance, half-rolled-out pilots, data trust issues) so they can be planned around rather than discovered the hard way.

Practical takeaways

  • Treat AI-mobile as a strategic differentiation lever for luxury, not a cost-saving experiment.
  • Build the full guest-journey stack: pre-arrival personalization → mobile check-in → digital key → smart-room controls → in-app requests/payments → loyalty → post-stay.
  • Deploy AI chatbots to absorb the routine 60–70% of guest queries, freeing front desk and concierge staff for high-touch moments.
  • Add multilingual AI translation if you serve international guests — it's a low-cost, high-impact satisfaction lever.
  • Install AI-driven HVAC and smart building controls — the 20–30% energy savings funds the rest of the digital roadmap.
  • Engineer a **hybrid service model**: automation for routine and back-office; human staff for emotional, complex, and recovery moments. Do not chase full automation in luxury.
  • Plan implementation explicitly: pilot before chain-wide rollout, train employees ahead of go-live, address job-security concerns directly, partner with vendors who know hospitality.
  • Be transparent about data: tell guests what you collect, let them control it, and earn the trust required for personalization to feel like value rather than surveillance.
  • Frame sustainability as dual benefit (margin + brand), not cost — and use the mobile app itself to message sustainability practices to guests.
  • Don't bolt mobile check-in onto legacy front-desk workflows. Without a holistic digital strategy, you get duplicative work and minimal gain.

Tags

Artificial IntelligenceHospitalityHotel OperationsGuest ExperiencePersonalizationOperationsSustainabilityHospitality TechnologyTechnology Adoption

Related research

Academic ResearchMay 31, 2026

The Effect of AI Chatbot Perceived Usefulness and Service Convenience on Customer Loyalty with Mediating Role of Customer Experience in Travel Agency Services

Survey of 200 online travel agency users in Jakarta who interacted with AI chatbots in the past six months, analyzed via PLS-SEM. Perceived usefulness and service convenience both drive customer loyalty in OTA chatbot interactions, with customer experience as a partial mediator that converts functional benefit into emotional commitment. The functional value of a chatbot alone does not create loyalty — it must first translate into a positive, personalized, accessible experience.

Academic ResearchJune 6, 2026

When Robots Speak: Exploring Conversational Styles, Robot Persona Realism, and Engagement in Hospitality and Tourism Services

Across one field study and three online experiments in restaurants, hotels, railways, and airports, the authors show that emotional conversational styles in AI service robots drive higher purchase intentions than rational styles, with engagement as the mediating mechanism. Robot persona realism moderates the effect: emotional styles work best with highly humanlike robots, while rational styles outperform with less anthropomorphic ones — a style-persona congruence rule for designing conversational AI in hospitality.

For Professors

Submit article for consideration

If you are a professor or researcher and would like to suggest a publicly available article for inclusion in the Research Hub, you can submit it for review and possible inclusion through our dedicated submission form.