The rapid integration of artificial intelligence (AI) and business intelligence (BI) tools into hotel operations is fundamentally reshaping what it means to manage in the U.S. hospitality industry. Research indicates that by 2030, robots and AI-enabled systems are expected to account for approximately 25% of the hospitality workforce (Bowen & Morosan, 2018). Yet while technology adoption continues to accelerate, limited scholarly attention has been paid to how managerial competencies must evolve in response. This paper conducts a systematic review of empirical and conceptual literature published between 2018 and 2025 on the intersection of AI adoption, data-driven decision-making, and managerial role transformation in U.S. hospitality operations. Drawing on Dynamic Capabilities Theory (Teece et al., 1997; Teece, 2007), the review synthesizes evidence across three thematic areas: the changing nature of the hospitality manager's role, the competencies required for effective human-AI collaboration, and the organizational barriers impeding managerial adaptation. Findings suggest that effective hospitality managers must increasingly blend digital literacy, data interpretation, and emotionally intelligent leadership to leverage AI tools without compromising the guest-centered service quality that defines the industry. Implications for hospitality education, operations management practice, and future research are discussed.