This protocol outlines a scoping review designed to systematically map the existing body of evidence on AI-enabled knowledge sharing in resource-limited non-profit healthcare organizations. The review aims to investigate how such technologies enhance collaboration and decision-making, particularly in the context of reduced external support following the cessation of USAID operations. Guided by three theoretical frameworks namely, the Resource-Based View, Dynamic Capabilities Theory, and Absorptive Capacity Theory, this study will explore the dual role of AI as a strategic resource and an enabler of organizational learning and agility. The protocol details a rigorous methodological approach based on PRISMA-ScR guidelines, encompassing a systematic search strategy across multiple databases, inclusion and exclusion criteria, and a structured data extraction process. By integrating theoretical insights with empirical evidence, this scoping review seeks to identify critical gaps in the literature and inform the design of effective, resource-optimized AI solutions in non-profit healthcare settings.

本研究旨在填补资源有限的非营利医疗组织中，人工智能知识共享对于协作与决策能力提升的研究空白。通过应用资源基础视角、动态能力理论和吸收能力理论，本文探讨了人工智能在组织学习和灵活性方面的双重作用。研究发现，结合理论与实证证据，可以识别文献中的关键空白，并为非营利医疗环境中有效、资源优化的人工智能解决方案的设计提供指导。

增强非营利医疗组织协作与决策能力的人工智能知识共享：范围评审协议