# Bridging perspectives: Success factors for AI implementation in healthcare from healthcare professionals and AI experts

## TL;DR

This study identifies success factors for AI in healthcare by comparing the views of healthcare professionals and AI experts, aiming to improve collaboration and sustainable adoption.

## Contribution

The study extends the NASSS framework to a dual-stakeholder context and proposes a framework to enhance collaboration between healthcare professionals and AI experts.

## Key findings

- Transparency leading to trust was the most emphasized success factor by both healthcare professionals and AI experts.
- Alignments were found in interorganizational cooperation, demand-side value, usability, and role redefinition.
- Gaps included cooperation challenges, data quality concerns, and limited attention to usability.

## Abstract

The integration of Artificial Intelligence (AI) in healthcare offers opportunities to transform patient care, improve efficiency, and support clinical decision-making. Yet, its implementation is hindered by technical, organizational, and collaborative challenges. This study explores the key success factors for sustainable AI adoption from the perspectives of healthcare professionals (HCPs) and AI experts, with the aim of identifying alignments and gaps that influence collaboration and sustainability.

Guided by the NASSS framework, semi-structured interviews were conducted with four HCPs and five AI experts with experience related to AI technologies in the healthcare sector. Thematic analysis was applied to examine stakeholder perspectives, focusing on gaps and alignments between stakeholders and identifying common patterns.

Transparency leading to trust was the most emphasized factor by both AI experts and HCPs. Alignments were also found in recognizing the importance of interorganizational cooperation, demand-side value, scope of use, usability, responsibility and redefining the roles. Gaps included challenges in cooperation with HCPs, misunderstandings between stakeholders and the need for interdisciplinary experts, insufficient training, concerns over data quality and privacy, and limited attention to usability. Based on the found patterns, a framework is proposed to strengthen collaboration between AI experts and HCPs, enabling effective and sustainable AI implementation in healthcare.

This study extends the NASSS framework to a dual-stakeholder context, offering insights into the alignments and gaps between HCPs and AI experts. The proposed framework supports improved collaboration, guiding healthcare professionals, AI developers, and managers toward effective, sustainable AI implementation and fostering mutual understanding for successful adoption.