biostudies-literatureSilvestro DSwiss National Science Foundation415-424https://www.ebi.ac.uk/biostudies/studies/S-EPMC7612764biostudies-literatureUnknown5(5)Over a million species face extinction, urging the need for conservation policies that maximize the protection of biodiversity to sustain its manifold contributions to people. Here we present a novel framework for spatial conservation prioritization based on reinforcement learning that consistently outperforms available state-of-the-art software using simulated and empirical data. Our methodology, CAPTAIN (Conservation Area Prioritization Through Artificial INtelligence), quantifies the trade-off between the costs and benefits of area and biodiversity protection, allowing the exploration of multiple biodiversity metrics. Under a limited budget, our model protects substantially more species from extinction than areas selected randomly or naively (such as based on species richness). CAPTAIN Nature sustainabilityImproving biodiversity protection through artificial intelligence.PMC7612764187012Sterner TAntonelli ASilvestro DGoria SfalseImproving biodiversity protection through artificial intelligence.Over a million species face extinction, urging the need for conservation policies that maximize the protection of biodiversity to sustain its manifold contributions to people. Here we present a novel framework for spatial conservation prioritization based on reinforcement learning that consistently outperforms available state-of-the-art software using simulated and empirical data. Our methodology, CAPTAIN (Conservation Area Prioritization Through Artificial INtelligence), quantifies the trade-off between the costs and benefits of area and biodiversity protection, allowing the exploration of multiple biodiversity metrics. Under a limited budget, our model protects substantially more species from extinction than areas selected randomly or naively (such as based on species richness). CAPTAIN 2022-01-01T00:00:00Z2022 May2025-04-21T21:24:13.102Z2025-02-19T04:04:54.576ZS-EPMC76127643561493310.1038/s41893-022-00851-6