| Sumario: | The increasing adoption of artificial intelligence applications in healthcare institutions necessitates the restructuring of managerial and operational processes. This study evaluates the integration of artificial intelligence into hospital management processes from the perspective of healthcare managers and examines its potential effects on operational efficiency, employees’ work practices, patient safety, and institutional sustainability. The study is structured on the basis of Socio-Technical Systems Theory and the Technology– Organization–Environment framework. Conducted using a phenomenological qualitative design, the research collected data through semi-structured interviews with nine healthcare managers working in public, private, and university hospitals, and analyzed the data through content analysis. The findings revealed fragmented processes, repetitive data entry, manual workload, and problems related to planning, billing, and inventory management. Participants stated that artificial intelligence could provide decision support, early warning, forecasting, and automation; however, they also noted risks such as data security, privacy, legal compliance, inadequate infrastructure, and employee resistance. The study offers a managerial contribution to the clinically focused literature by proposing an applicable artificial intelligence roadmap from the perspective of healthcare managers. The study concludes that artificial intelligence integration in healthcare institutions should not be regarded merely as a technical investment, but as a socio-technical transformation that requires data governance, managerial commitment, employee acceptance, ethical oversight, and continuous improvement. In this respect, the study contributes to the healthcare management literature by proposing a managerially grounded and practically applicable roadmap for artificial intelligence integration.
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