Leading Through Change: A Conceptual Model of AI Adoption and Job Satisfaction in the Tourism Industry

Abstract

As artificial intelligence (AI) becomes increasingly integrated into the tourism industry, leadership plays a critical role in shaping how employees perceive and adapt to technological change. This conceptual study proposes a framework that examines the influence of transformational and transactional leadership styles on job satisfaction in AI-integrated tourism organizations. Drawing upon the Technology Acceptance Model (TAM) and leadership theories, the model posits that the perceived usefulness of AI serves as a key mediating variable linking leadership behaviors to employee outcomes. It is theorized that transformational leadership enhances job satisfaction more significantly than transactional leadership by fostering innovation, alignment with AI-driven goals, and a supportive organizational climate. Transactional leadership, while valuable for operational clarity and short-term objectives, is expected to have a comparatively limited effect on employee satisfaction. The framework contributes to the theoretical understanding of how leadership styles facilitate digital transformation and employee well-being in service-oriented industries. It offers practical insights for tourism leaders seeking to optimize AI adoption while maintaining a human-centered workplace culture.