ASSESSING THE ADOPTION OF AI-DRIVEN AUTOMATION IN HEALTHCARE

Abstract

The integration of artificial intelligence (AI) and automation in healthcare presents a transformative potential for improving operational efficiency, patient outcomes, and clinical decision-making processes. This study explores the factors influencing the adoption of AI-driven automation technologies within healthcare settings. By employing a mixed-methods approach, we gather quantitative data through surveys and qualitative insights from interviews with healthcare professionals and administrators. The findings reveal that while there is a growing interest in AI applications, several barriers impede widespread implementation, including concerns about data privacy, the need for staff training, and the integration with existing systems. This research underscores the importance of addressing these challenges to facilitate a smoother transition towards automated healthcare solutions. Moreover, it highlights the need for collaborative efforts among stakeholders to develop strategies that enhance the acceptance and effectiveness of AI technologies in healthcare.