Situating AI in Environmental Science: Perspectives Across Sectors and Career Stages

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint. You must log in to post a comment. There are no comments or no comments have been made public for this article. This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint. Add a Comment You must log in to post a comment. Comments There are no comments or no comments have been made public for this article. The use of Artificial Intelligence (AI) is rapidly proliferating across career sectors, including those in the environmental sciences. The field’s reliance on technical analysis, complex and multidimensional datasets, and broad interdisciplinary job responsibilities makes it well-suited to benefit from advancements in AI. However, careers within environmental science are highly diverse and the opportunities and limitations of AI use across these sectors are uneven. We present a first-hand interdisciplinary perspective on these unique opportunities and limitations across roles, career types, and career stages in the environmental sciences. We find that the use of AI has strong potential to augment training, accelerate research workflows, and support resource management by automating routine or labor-intensive computational tasks. At the same time, these tools pose substantive challenges for faculty preparing new graduates for a rapidly evolving technical workforce and for scientists working to maintain standards across the research process as output increases. Differential access, incentives, and norms of use across career types and stages may also disrupt mentorship structures and introduce new barriers to some forms of interdisciplinary collaboration even as others become more tractable. Additionally, for a discipline focused on the environment, the water consumption, energy use, and other societal impacts of the data centers that enable frontier large language models present a sizable, if still rather quantitatively unconstrained, moral concern. In total, the expanding adoption of AI approaches has the potential to produce significant progress in our understanding and management of natural systems. However, careful consideration is required to evaluate the implications of its rapid, uneven, and continually evolving integration across the environmental science profession. Proactively identifying and addressing these limitations will be essential to mitigating unintended consequences and maximizing positive impact. https://doi.org/10.32942/X25M24 Biotechnology Artificial Intelligence; Environmental Sciences; Conservation Published: 2026-03-25 13:03 Last Updated: 2026-03-25 13:03 CC BY Attribution 4.0 International Language: English