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Yet, the accelerating growth and heterogeneity of environmental literature are increasingly exceeding the capacity of conventional manual workflows. Here, we conducted an expert-led systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance to assess the capabilities, reliability boundaries, and real-world applications of artificial intelligence (AI)-assisted EESs. From 38,840 records, we included 459 peer-reviewed studies and organized them into three evidence streams. Capability evidence revealed a substantial but weakly EES-adapted AI tool ecosystem with 158 directly usable tools but only three directly relevant to EES, indicating that environment-specific capabilities remain scarce and task-localized. Reliability evidence showed task-contingent AI performance, with more stable outputs for structured front-end tasks but persistent verification needs for judgment-intensive tasks. Real-world evidence shows that AI has already entered evidence synthesis practice, but its use in EES is advancing ahead of domain-specific validation. Together, these findings indicate that AI-assisted EES is moving from possibility to practice but not yet from adoption to trust. This transition will require trustworthy AI-assisted EES infrastructure, including task-specific environmental tools, expert-annotated benchmarks, transparent reporting and validation standards, and living EES systems for continuous updates. Only within such an infrastructure can AI move beyond a tool for efficiency gains and become a governed, credible capability for environmental knowledge production.<\/jats:p>","DOI":"10.1021\/acs.est.6c09347","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T16:29:34Z","timestamp":1788452974000},"page":"25110-25127","source":"Crossref","is-referenced-by-count":0,"title":["From\nAdoption to Trust in AI-Assisted Environmental\nEvidence Synthesis: A Systematic Review of Capabilities, Reliability\nBoundaries, and Real-World Applications"],"prefix":"10.1021","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1217-4588","authenticated-orcid":true,"given":"Haoyue","family":"Tan","sequence":"first","affiliation":[{"name":"Nanjing University , , , ,","place":["Nanjing, Jiangsu, China, 210023"]},{"name":"Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk , , ,","place":["Nanjing, Jiangsu, China, 210023"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingjie","family":"Bin","sequence":"additional","affiliation":[{"name":"Nanjing University , , , ,","place":["Nanjing, Jiangsu, China, 210023"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfeng","family":"Fang","sequence":"additional","affiliation":[{"name":"National University of Singapore , , ,","place":["Singapore, Singapore, 119077"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3430-1189","authenticated-orcid":true,"given":"Chao","family":"Fang","sequence":"additional","affiliation":[{"name":"Nanjing University , , , ,","place":["Nanjing, Jiangsu, China, 210023"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9499-818X","authenticated-orcid":true,"given":"Wei","family":"Shi","sequence":"additional","affiliation":[{"name":"Nanjing University , , , ,","place":["Nanjing, Jiangsu, China, 210023"]},{"name":"Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk , , ,","place":["Nanjing, Jiangsu, China, 210023"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,9,2]]},"reference":[{"key":"2026091511112484900_cit1","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1126\/science.abd6951","article-title":"A ubiquitous tire rubber\u2013derived\nchemical induces acute mortality in coho salmon","volume":"371","author":"Tian","year":"2021","journal-title":"Science"},{"key":"2026091511112484900_cit2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abe8244","article-title":"From cohorts to molecules:\nadverse impacts of endocrine disrupting mixtures","volume":"375","author":"Caporale","year":"2022","journal-title":"Science"},{"key":"2026091511112484900_cit3","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1038\/s41586-024-08375-z","article-title":"One-quarter of freshwater\nfauna threatened with extinction","volume":"638","author":"Sayer","year":"2025","journal-title":"Nature"},{"key":"2026091511112484900_cit4","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1038\/s41893-019-0442-8","article-title":"Addressing environmental\nsustainability of biochemicals","volume":"3","author":"O\u0308gmundarson","year":"2020","journal-title":"Nat. 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Med."},{"key":"2026091511112484900_cit20","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0227742","article-title":"Error rates of human\nreviewers during abstract screening in systematic reviews","volume":"15","author":"Wang","year":"2020","journal-title":"PLoS One"},{"key":"2026091511112484900_cit21","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.jclinepi.2020.01.005","article-title":"Single-reviewer\nabstract\nscreening missed 13% of relevant studies: a crowd-based, randomized\ncontrolled trial","volume":"121","author":"Gartlehner","year":"2020","journal-title":"J. Clinical Epidemiol."},{"key":"2026091511112484900_cit22","doi-asserted-by":"publisher","first-page":"1975","DOI":"10.1007\/s11301-024-00471-8","article-title":"What is\nthe future of human-generated systematic\nliterature reviews in an age of artificial intelligence?","volume":"74","author":"Block","year":"2024","journal-title":"Management Rev. Quarterly"},{"key":"2026091511112484900_cit23","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1038\/s42256-025-01020-y","article-title":"AI safety for everyone","volume":"7","author":"Gyevna\u0301r","year":"2025","journal-title":"Nat. Machine Intelligence"},{"key":"2026091511112484900_cit24","unstructured":"Kitchenham, B. C.\n          \n          Guidelines\nfor Performing Systematic Literature Reviews in Software Engineering\nEBSE Technical Report EBSE-2007\u201301, School of Computer Science And Mathematics, Keele University2007."},{"key":"2026091511112484900_cit25","doi-asserted-by":"publisher","DOI":"10.1111\/jep.70100","article-title":"Digital tools to support\nthe systematic review process: an introduction","volume":"31","author":"Schmidt","year":"2025","journal-title":"J. Evaluat. Clinical Practice"},{"key":"2026091511112484900_cit26","doi-asserted-by":"crossref","unstructured":"Adam, G. P.; Davies, M.; George, J.; et al.\n          Machine\nLearning Tools to (Semi-)automate Evidence Synthesis: A Rapid Review\nand Evidence Map. Research White Paper, 2025.","DOI":"10.23970\/AHRQEPCWHITEPAPERMACHINE2"},{"key":"2026091511112484900_cit27","doi-asserted-by":"publisher","DOI":"10.1002\/jcv2.12234","article-title":"How to optimize the\nsystematic review process using AI tools","volume":"4","author":"Fabiano","year":"2024","journal-title":"JCPP\nAdv."},{"key":"2026091511112484900_cit28","doi-asserted-by":"publisher","first-page":"195","DOI":"10.5195\/jmla.2020.834","article-title":"Improving the translation\nof search strategies using the Polyglot Search Translator: a randomized\ncontrolled trial","volume":"108","author":"Clark","year":"2020","journal-title":"J. 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Evolution"},{"key":"2026091511112484900_cit31","doi-asserted-by":"publisher","DOI":"10.1016\/j.mex.2022.101935","article-title":"An automated method\nfor developing search strategies for systematic review using Natural\nLanguage Processing (NLP)","volume":"10","author":"Kwabena","year":"2023","journal-title":"MethodsX"},{"key":"2026091511112484900_cit32","doi-asserted-by":"publisher","DOI":"10.1002\/cesm.12078","article-title":"The searchbuildR shiny\napp: A new implementation of the objective approach for search strategy\ndevelopment in systematic reviews","volume":"2","author":"Kapp","year":"2024","journal-title":"Cochrane\nEvidence Synthesis Methods"},{"key":"2026091511112484900_cit33","doi-asserted-by":"publisher","first-page":"420","DOI":"10.3390\/info16050420","article-title":"PROMPTHEUS: a human-centered\npipeline to streamline systematic literature reviews with large language\nmodels","volume":"16","author":"Torres","year":"2025","journal-title":"Information"},{"key":"2026091511112484900_cit34","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1038\/s41746-025-01840-7","article-title":"Accelerating clinical evidence synthesis with\nlarge language models","volume":"8","author":"Wang","year":"2025","journal-title":"npj Digital Medicine"},{"key":"2026091511112484900_cit35","unstructured":"Elicit.\n          . Available at https:\/\/elicit.com\/?q=Web3 (accessed 2026\u201308\u201327)."},{"key":"2026091511112484900_cit36","unstructured":"Semantic Scholar.\n          . Available at https:\/\/www.semanticscholar.org\/ (accessed 2026\u201308\u201327)."},{"key":"2026091511112484900_cit37","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1080\/09737766.2022.2106167","article-title":"Research discovery and\nvisualization using ResearchRabbit: A use case of AI in libraries","volume":"16","author":"Sharma","year":"2022","journal-title":"COLLNET Journal of Scientometrics and Information Management"},{"key":"2026091511112484900_cit38","unstructured":"Consensus.\n          . Available at https:\/\/consensus.app\/ (accessed\n2026\u201308\u201327)."},{"key":"2026091511112484900_cit39","unstructured":"Web of Science Research Assistant.\n          . 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In  Proceedings of the First Instructional Conference on Machine Learning, 2003."},{"key":"2026091511112484900_cit42","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/s10664-021-10084-4","article-title":"SeSG: a search string\ngenerator for Secondary Studies with hybrid search strategies using\ntext mining","volume":"27","author":"Alves","year":"2022","journal-title":"Empirical Software Eng."},{"key":"2026091511112484900_cit43","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1038\/s42256-020-00287-7","article-title":"An open\nsource machine learning framework for efficient and transparent systematic\nreviews","volume":"3","author":"van de Schoot","year":"2021","journal-title":"Nat. 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Int."},{"key":"2026091511112484900_cit45","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1186\/s12911-019-0992-8","article-title":"Improving reference\nprioritisation with PICO recognition","volume":"19","author":"Brockmeier","year":"2019","journal-title":"BMC Med.\nInformatics Decision Making"},{"key":"2026091511112484900_cit46","doi-asserted-by":"publisher","DOI":"10.1093\/jamiaopen\/ooac107","article-title":"Not so weak PICO: leveraging weak supervision\nfor participants, interventions, and outcomes recognition for systematic\nreview automation","volume":"6","author":"Dhrangadhariya","year":"2023","journal-title":"JAMIA Open"},{"key":"2026091511112484900_cit47","doi-asserted-by":"publisher","DOI":"10.3389\/frai.2025.1662202","article-title":"Analysis of article\nscreening and data extraction performance by an AI systematic literature\nreview platform","volume":"8","author":"Cassell","year":"2025","journal-title":"Front. Artificial Intelligence"},{"key":"2026091511112484900_cit48","doi-asserted-by":"crossref","unstructured":"Mao, X.; et al.\n          AiReview:\nan open platform for accelerating systematic reviews with LLMs. In  Proceedings of the 48th International ACM SIGIR Conference\non Research and Development in Information Retrieval; Association for Computing Machinery, 2025.","DOI":"10.1145\/3726302.3730133"},{"key":"2026091511112484900_cit49","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1186\/s13643-016-0384-4","article-title":"Rayyan\u2500a web\nand mobile app for systematic reviews","volume":"5","author":"Ouzzani","year":"2016","journal-title":"Systematic\nReviews"},{"key":"2026091511112484900_cit50","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1186\/s13643-019-1221-3","article-title":"Assessing the accuracy\nof machine-assisted abstract screening with DistillerAI: a user study","volume":"8","author":"Gartlehner","year":"2019","journal-title":"Systemat. Rev."},{"key":"2026091511112484900_cit51","unstructured":"USEPA.\n          \n          Health Assessment\nWorkspace Collaborative (HAWC). Available at https:\/\/www.epa.gov\/risk\/health-assessment-workspace-collaborative-hawc (accessed 2026\u201308\u201327)."},{"key":"2026091511112484900_cit52","doi-asserted-by":"publisher","first-page":"1524","DOI":"10.1021\/acs.chemrestox.4c00134","article-title":"Toward an explainable large language model\nfor the automatic identification of the drug-induced liver injury\nliterature","volume":"37","author":"Ma","year":"2024","journal-title":"Chem. Res. Toxicol."},{"key":"2026091511112484900_cit53","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2019.105228","article-title":"Novel text analytics\napproach to identify relevant literature for human health risk assessments:\nA pilot study with health effects of in utero exposures","volume":"134","author":"Cawley","year":"2020","journal-title":"Environ. Int."},{"key":"2026091511112484900_cit54","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1093\/jamia\/ocv044","article-title":"RobotReviewer:\nevaluation\nof a system for automatically assessing bias in clinical trials","volume":"23","author":"Marshall","year":"2016","journal-title":"J. Am. Med. Informatics Association"},{"key":"2026091511112484900_cit55","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1186\/1472-6947-10-56","article-title":"ExaCT: automatic extraction\nof clinical trial characteristics from journal publications","volume":"10","author":"Kiritchenko","year":"2010","journal-title":"BMC Med. Informatics Decision Making"},{"key":"2026091511112484900_cit56","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2021.107025","article-title":"Evaluation of a semi-automated\ndata extraction tool for public health literature-based reviews: Dextr","volume":"159","author":"Walker","year":"2022","journal-title":"Environ. 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