Key success factors in AI implementation in healthcare, from the perspectives of healthcare professionals and AI experts

The integration of Artificial Intelligence (AI) in healthcare holds immense potential to revolutionize patient care, improve operational efficiency, and enhance decision-making processes. However, its successful implementation remains challenging due to technical, organizational, and collaborative barriers. This study investigates the key success factors for AI implementation in healthcare, focusing on the perspectives of two critical stakeholder groups: healthcare professionals (HCPs) and AI experts. Using the NASSS (Nonadoption, Abandonment, Scale-up, Spread, and Sustainability) framework as a foundation, the study explores the alignment and gaps between these groups, aiming to provide actionable insights for enhancing collaboration and adoption.

The research employs a qualitative methodology, conducting semi-structured interviews with nine participants—four healthcare professionals and five AI experts—based in Finland. The questions are driven by the NASSS framework based on their relevance to this study and the stakeholders of research. Thematic analysis was used to analyse the data, identifying gaps, alignments and the patterns. Key findings reveal that both groups emphasize the importance of transparency and trust, cooperation between the two stakeholders especially involving healthcare professionals from the early stages in the tool development. Moreover, the demand-side value, ease of use, understanding the scope of use by healthcare providers, the quality of training data emerged as critical factors in the relationship between them.

A significant contribution of this study is the development of a tailored framework to bridge the gaps between healthcare professionals and AI experts. The framework offers practical guidance for fostering interdisciplinary collaboration, better understanding the demand-side value and improvement in the perceived value besides transparency of the AI tool and training, which all enhance the trust and collaboration.

The findings contribute to both theoretical and practical domains. Theoretically, this study extends the application of the NASSS framework to stakeholder collaboration in AI implementation, providing new insights into its dynamics. Practically, it offers actionable strategies for healthcare managers, AI developers, and decision makers to overcome challenges and facilitate effective adoption. By addressing the complexities of collaboration and implementation, this research highlights the pathways for successful AI integration in healthcare through improvement in collaboration between healthcare professionals and AI experts, ultimately supporting improved patient outcomes and operational efficiency.