Balancing Care and Cost: A Qualitative Exploration of Healthcare Professionals' Perspectives on Artificial Intelligence‐Supported Efficiency and Perceived Financial Implications in Healthcare

ABSTRACT Background Artificial intelligence (AI) is increasingly integrated into healthcare systems to support efficiency, cost management, and decision‐making. However, less is known about how healthcare professionals perceive these changes in routine practice, particularly in resource‐constrained settings. Because this study did not collect objective financial, accounting, utilization, or institutional performance data, financial findings are interpreted as perceived financial implications rather than measured outcomes. Aim This study aimed to explore healthcare professionals' perspectives on AI‐supported efficiency, perceived financial implications, and patient‐centered care within healthcare environments. Methods A qualitative descriptive study with an interpretive orientation was conducted in two private tertiary hospitals in Dhaka, Bangladesh. A total of 32 participants, including physicians, nurses, administrators, and health informatics professionals, were recruited through purposive and snowball sampling. Data were collected through semi‐structured interviews conducted between January and February 2026 and analyzed using thematic analysis with inductive and deductive coding. Results Five major themes emerged. Participants perceived AI‐supported functions, including documentation and reporting automation, scheduling, task prioritization, initial assessment and data organization, and decision support, as helping to streamline workflows. They also perceived potential resource optimization and reductions in unnecessary expenditure, while emphasizing high initial investment, maintenance costs, and delayed financial returns. Human‐centered care, professional judgement, trust, training, infrastructure, and organizational policy shaped how these perceived benefits and burdens were experienced. Conclusion Healthcare professionals in the two participating hospitals perceived AI‐supported systems as having potential to improve workflow efficiency and resource use, but these perceived benefits were conditional on infrastructure, training, governance, professional oversight, and preservation of patient‐centered care. The findings represent participants' experiences and perceptions and do not demonstrate objective cost savings, financial sustainability, or causal effects.