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arXiv cs.AI · Dalia Ali, Muneeb Ahmed, Hailan Wang, Arfa Khan, Naira Paola Arnez Jordan, Sunnie S. Y. Kim, Meet Dilip Muchhala, Anne Kathrin Merkle, Orestis Papakyriakopoulos · 2026-09-29 AI

[Submitted on 4 Oct 2025 (v1), last revised 27 Sep 2026 (this version, v2)]

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Abstract:Despite AI’s promise, little is known about how mission-driven organizations (MDOs) adopt AI. We conducted semi-structured interviews with 15 experts and leaders within environmental, humanitarian, and development organizations across the Global North and South. We find that MDOs adopt AI selectively, with uses in content creation and data analysis, while maintaining human oversight for mission-critical applications. In case of conflicts between the organization’s values and efficiency, participants consider sustainability, neutrality, and community trust as constraints that could limit or prevent AI adoption. Individual adoption of AI is not translated into organizational practice due to fragmented data infrastructure, lack of in-house expertise, inertia, ethical challenges, and dependency on vendors. Participants expected AI use in MDOs to involve institutional control over infrastructure, support for missions, and human-centered human-AI collaboration. We contribute an analysis on how MDOs manage AI adoption, identify barriers to responsible deployment, and provide recommendations for designing mission-aligned AI systems.

Submission history

From: Dalia Ali [view email]
[v1] Sat, 4 Oct 2025 16:28:54 UTC (4,197 KB)
[v2] Sun, 27 Sep 2026 14:07:54 UTC (208 KB)

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추출 본문 · 출처: arxiv.org · https://arxiv.org/abs/2510.03868