Individual dynamic capabilities and artificial intelligence in health operations: Exploration of innovation diffusion

This research investigates the integration of individual dynamic capabilities (IDC), artificial intelligence (AI), and the Technology Acceptance Model (TAM) within health operations to evaluate their role in fostering innovation diffusion in healthcare. A convergent, multifaceted research approach encompassing quantitative and qualitative methodologies was employed, commencing with a systematic review of the extant literature. This was then complemented by the execution of focus group sessions involving 21 participants. The main objective of this sequential exploratory design was to synthesize existing research present an empirical validation of real-world case studies, and assess AI deployment challenges that influence operational efficiency and service quality in healthcare organizations. The findings underscore the importance of IDC in advancing healthcare practices by driving cross-functional adaptation, facilitating AI implementation, and ensuring smooth operational transformation in line with healthcare standards and best practices. The findings offer valuable insights for operational and executive-level decision-makers aiming to optimize health operations by integrating IDC and AI technologies, enhancing patient care, service quality, and innovative health solutions. • Integration of AI and IDC enhances healthcare operational efficiency and regulatory compliance. •Individual dynamic capabilities foster adaptability, technological adoption, and continuous learning in healthcare operations. •AI-driven predictive analytics streamline decision-making and improve patient care outcomes. •IDC and AI synergistically optimize data interoperability and regulatory standards in healthcare systems. •Leadership commitment and cross-functional collaboration drive successful AI and IDC implementation.