<![CDATA[The rapid adoption of artificial intelligence (AI) in the hospitality industry has intensified expectations regarding service efficiency, personalization, and operational performance. Despite growing empirical evidence highlighting the potential benefits of AI-enabled systems, implementation outcomes across hotel contexts remain uneven. This inconsistency suggests that technological capability alone is insufficient to explain project success, underscoring the need to examine AI adoption through the lens of information technology (IT) project management. Accordingly, this study investigates how AI-driven IT projects contribute to operational efficiency in the hospitality sector and identifies managerial and organizational factors that differentiate successful implementations from those that underperform or fail. A structured literature review (SLR) was conducted to synthesize recent empirical and conceptual studies on AI implementation in hotel operations. The analysis focuses on operational performance outcomes across guest-facing and organizational domains, as well as contextual conditions shaping project execution. The results indicate that AI-driven IT projects are commonly associated with improvements in service responsiveness, personalization accuracy, internal workflow efficiency, and resource utilization. However, the magnitude and sustainability of these benefits vary considerably across implementation contexts. An aggregated analysis of operational outcomes reveals that projects achieving balanced improvements across both service and organizational dimensions tend to demonstrate more stable efficiency gains. The findings further highlight leadership commitment, stakeholder engagement, change management practices, and system integration depth as critical determinants of project success. By framing AI adoption as a socio-technical IT project rather than a standalone technological upgrade, this study contributes to the hospitality and information systems literature and offers actionable insights for managers seeking to align AI initiatives with organizational strategy and service delivery objectives]]>
