研究非营利组织如何在资源有限下谨慎使用AI，发现其应用受限于价值观而非技术。
AI Adoption Across Mission-Driven Organizations
- 通过访谈15位从业者，分析环保、人道等组织的AI实际应用与障碍。
- AI多用于内容生成和数据分析，关键决策仍依赖人工，避免价值冲突。
- 强调组织自主性与使命完整性，适合关注社会影响的AI实践者参考。
尽管人工智能有望应对全球挑战，但对其在使命驱动型组织（MDOs）中的采纳情况，实证研究仍十分有限。现有研究多聚焦个体应用或伦理原则，缺乏对资源受限、价值观导向组织如何在运营中整合AI的理解。本研究对来自全球南北地区的环境、人道主义与发展组织的15位实践者进行了半结构化访谈，开展主题分析，探讨MDOs当前如何部署AI、面临哪些制约因素，以及对未来整合的设想。研究发现，MDOs对AI采取选择性采纳策略：在内容创作和数据分析中实现较复杂应用，但在核心任务上保持人类监督。当AI的效率优势与组织价值观冲突时，决策往往停滞而非权衡取舍。本研究提供了实证证据，表明MDO中的AI采纳是条件性的，仅在增强组织自主权和使命完整性、并维持以人为本方法时才可行。
原文摘要 · Abstract (English)
Despite AI's promise for addressing global challenges, empirical understanding of AI adoption in mission-driven organizations (MDOs) remains limited. While research emphasizes individual applications or ethical principles, little is known about how resource-constrained, values-driven organizations navigate AI integration across operations. We conducted thematic analysis of semi-structured interviews with 15 practitioners from environmental, humanitarian, and development organizations across the Global North and South contexts. Our analysis examines how MDOs currently deploy AI, what barriers constrain adoption, and how practitioners envision future integration. MDOs adopt AI selectively, with sophisticated deployment in content creation and data analysis while maintaining human oversight for mission-critical applications. When AI's efficiency benefits conflict with organizational values, decision-making stalls rather than negotiating trade-offs. This study contributes empirical evidence that AI adoption in MDOs should be understood as conditional rather than inevitable, proceeding only where it strengthens organizational sovereignty and mission integrity while preserving human-centered approaches essential to their missions.
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