Reimagining artificial intelligence applications for Indigenous‐led community‐based wildlife monitoring: Insights from biodiversity surveys in the Warddeken Indigenous protected area in northern Australia

Abstract Although conservation science and practice increasingly rely on Artificial Intelligence (AI) wildlife monitoring tools, there is also growing recognition that effective and inclusive conservation depends on collaboration with Indigenous communities. Yet, approaches to guide how AI tools and insights can support Indigenous‐led community‐based monitoring (ICBM) goals remain underexplored. In this paper, we draw on insights from the Indigenous‐led Mayh wildlife ICBM program in Australia's Warddeken Indigenous Protected Area to highlight how the implementation of AI and data‐management tools can support language revitalization and clan‐based ICBM goals and ensure AI does not undermine local Indigenous governance and stewardship systems. We show why and how AI–ICBM partnerships need to be framed as ongoing collaborations that enable culturally situated decision‐making, empower Indigenous communities to guide technology development in ways that respect and align with values, support intergenerational knowledge transfer, and reimagine kin relationships between people, country, data, and animals.