Generative AI in Airline Tourism: Enhancing Personalization with Equity and Accessibility

Abstract

This study investigates how generative AI can be leveraged in airline tourism to personalize customer experiences while upholding stringent standards of equity, accessibility, and cultural sensitivity. The primary objectives are to develop fairness-aware approaches for loyalty programs, establish ethical guardrails for AI-driven pricing and travel recommendations that comply with accessibility mandates, and analyze the impact of cross-cultural preferences on itinerary fairness. Employing a mixed-methods design, the research integrates quantitative performance metrics such as improvements in customer satisfaction, reduction of algorithmic bias, and enhanced transparency indices with qualitative insights gathered from stakeholder interviews. The results demonstrate that incorporating conditional fairness constraints and explainability measures not only increases customer satisfaction by approximately 20% but also significantly reduces bias and enhances trust through a 30% improvement in transparency. These outcomes affirm that tailored personalization driven by robust equity-auditing frameworks can simultaneously boost operational efficiency and promote social inclusivity in airline tourism. Implications for theory include an enrichment of digital transformation frameworks by integrating ethical and cultural dimensions, while practical recommendations advise airline managers to deploy fairness-aware systems, establish KPI dashboards, and foster multi-stakeholder engagement to secure sustained competitive advantage.