Short answer

When designing or implementing Generative AI solutions in hospitality, prioritize a balanced approach that actively considers and integrates the needs and experiences of both customers and the workforce.

Field
User-Centred Design
Source
Tourism Review (2026)
Method
Systematic Literature Review
Sample
89 studies
Evidence
Moderate effect

Generative AI's impact on the hospitality and tourism sector is a complex interplay between enhancing customer experience and influencing workforce dynamics, requiring a holistic approach to value co-creation. This user-centred design research insight is drawn from a 2026 study published in Tourism Review. Using Systematic literature review with 89 studies, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing or implementing Generative AI solutions in hospitality, prioritize a balanced approach that actively considers and integrates the needs and experiences of both customers and the workforce.

Study
User-Centred DesignNew This WeekModerate effect

Generative AI Integration in Hospitality: Balancing Tourist Delight with Workforce Well-being

Generative AI's impact on the hospitality and tourism sector is a complex interplay between enhancing customer experience and influencing workforce dynamics, requiring a holistic approach to value co-creation.

Tourism Review · 2026

01

Key Findings

  • 01Existing research on Generative AI in hospitality is fragmented and predominantly customer-centric.
  • 02Guest expectations and workforce responses to Generative AI are mutually constitutive.
  • 03Generative AI's impact can be conceptualized through three emergent modes of interaction: alignment, divergence, and negotiation.
02

Application

Design takeaway

When designing or implementing Generative AI solutions in hospitality, prioritize a balanced approach that actively considers and integrates the needs and experiences of both customers and the workforce.

How to apply

Before deploying a new Generative AI tool for customer service, conduct parallel research into its potential impact on staff roles, training needs, and job satisfaction. Involve frontline staff in the design and testing phases.

Project actions

  • 01When researching AI applications, ensure you investigate both user acceptance and potential workforce implications.
  • 02Consider how your design choices might affect different user groups (customers vs. staff) and how they might interact with the technology.
03

Method & Evidence

AimHow does the integration of Generative AI in the hospitality and tourism industry affect both tourist experience and workforce dynamics, and how can these interactions be managed for value co-creation?
MethodSystematic Literature Review
ProcedureA systematic review was conducted on 89 peer-reviewed studies published since 2023 to map theoretical approaches, methodological trends, contextual features, and key findings related to Generative AI in hospitality and tourism.
Sample89 studies
ContextHospitality and Tourism Industry

Variables

IVGenerative AI integration in hospitality and tourism
DVTourist experience dynamics, Workforce experience dynamics, Value co-creation
CVSpecific AI technologies, types of hospitality businesses, geographical locations, existing industry practices
04

Strengths & Limitations

Strengths

  • +Provides a novel, integrated lens for understanding AI's systemic effects.
  • +Links micro-level dynamics (trust, deskilling) with macro-outcomes (service quality, loyalty).

Limitations

The literature review might not capture the very latest, cutting-edge AI developments or real-world implementations that haven't yet been published. The findings are generalized across the hospitality and tourism sector and may not apply equally to all specific contexts.

Reliability & validity

The reliability of the findings relies on the systematic nature of the literature review process. Validity is enhanced by synthesizing a broad range of studies, but the inherent biases within the reviewed literature may affect the overall validity of the conclusions.

Think critically

Given the fragmented nature of current research, how can designers proactively identify and mitigate potential negative impacts of Generative AI on the hospitality workforce, even before widespread adoption and documented evidence emerge?

05

Design Principles

"Holistic AI Integration: Design and implement AI systems by considering the interconnected impacts on all stakeholders, ensuring that enhancements in one area do not detract from another."

Designers and engineers must consider the dual nature of Generative AI implementation. A focus solely on customer-facing applications risks overlooking potential negative impacts on staff, leading to suboptimal service delivery and employee dissatisfaction. Understanding these interconnected dynamics is crucial for successful and sustainable technology adoption.

06

What This Means for Your Design

When you think about using AI in hotels or restaurants, remember it's not just about making things easier for guests. It also changes how people who work there do their jobs. You need to think about both sides to make it work well.

How to use in your project

  • 1.Reference this study when discussing the broader impacts of technology adoption beyond immediate user benefits, particularly in service industries.
  • 2.Use the 'Tourist Experience–Workforce Dynamics' framework to analyze how your own design choices might affect different user groups.
07

Add to My Project

08

Quick Cite

Paragraph starter

This research highlights the critical need to consider the dual impact of Generative AI on both tourist experience and workforce dynamics within the hospitality and tourism sector. By moving beyond a singular focus on customer-centricity, designers can develop more integrated solutions that foster value co-creation through alignment, divergence, and negotiation between guest expectations and workforce responses.

09

Source

Tourism Review

Generative AI in hospitality and tourism: a dual-stakeholder perspective on tourist and workforce experience dynamics

journal · 2026

View source

Questions About This Research

What does the research say about generative ai integration in hospitality: balancing tourist delight with workforce well-being?
When designing or implementing Generative AI solutions in hospitality, prioritize a balanced approach that actively considers and integrates the needs and experiences of both customers and the workforce. Evidence: Tourism Review (2026).
Why does "Generative AI Integration in Hospitality: Balancing Tourist Delight with Workforce Well-being" matter for design?
Designers and engineers must consider the dual nature of Generative AI implementation. A focus solely on customer-facing applications risks overlooking potential negative impacts on staff, leading to suboptimal service delivery and employee dissatisfaction. Understanding these interconnected dynamics is crucial for successful and sustainable technology adoption.
How can designers apply this research?
When designing or implementing Generative AI solutions in hospitality, prioritize a balanced approach that actively considers and integrates the needs and experiences of both customers and the workforce.
What were the main findings?
Existing research on Generative AI in hospitality is fragmented and predominantly customer-centric.. Guest expectations and workforce responses to Generative AI are mutually constitutive.. Generative AI's impact can be conceptualized through three emergent modes of interaction: alignment, divergence, and negotiation.
What research method was used?
Systematic Literature Review with 89 studies.
How strong is the evidence?
Evidence strength is rated Moderate effect, based on a 2026 journal from Tourism Review.
What should I do differently in my next project?
Before deploying a new Generative AI tool for customer service, conduct parallel research into its potential impact on staff roles, training needs, and job satisfaction. Involve frontline staff in the design and testing phases.
What are the limitations?
The study's findings are based on a review of existing literature, which may reflect existing biases in research focus and methodology. The rapid evolution of Generative AI means that current research may not fully capture future impacts.