{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T06:27:00Z","timestamp":1786688820510,"version":"build-2736575974"},"reference-count":17,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:00:00Z","timestamp":1786665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>\n                    Artificial intelligence is becoming a general-purpose enabling technology for the life sciences. AI-enabled tools can strengthen biosecurity and biodefense by improving early warning, accelerating vaccine and therapeutic discovery, supporting laboratory safety, and enabling more adaptive preparedness systems. However, these same tools may be a potential amplifier of misuse. The 2025 National Academies\u2019 report\n                    <jats:italic>The Age of AI in the Life Sciences: Benefits and Biosecurity Considerations<\/jats:italic>\n                    provides an important foundation for this analysis of the \u201ccapability uplift\u201d enabled by AI across the design\u2013build\u2013test\u2013learn (DBTL) cycle. \u201cCapability uplift,\u201d or \u0394AI, is a term used in the report to assess how AI-enabled biological tools can uniquely, and in some cases, specifically enable increases in or changes to biosecurity risks. The report proposes an \u201cif\u2013then\u201d approach to monitor emerging capabilities through observable indicators such as new datasets as the leading indicator of capability, model performance, and the erosion of build\/test barriers. Since the report\u2019s publication, agentic AI systems, virtual scientific teams, genome-scale foundation models, and self-driving laboratories have advanced from largely prospective concerns to early demonstrations. Multi-agent systems have been reported for biomedical hypothesis generation, design, and semi-autonomous discovery workflows, while self-driving laboratories now are considered as practical platforms for biotechnology. This perspective article extends these insights by employing a conceptual framework analysis and involves: (1) categorizing key AI capabilities across the DBTL cycle into a layered capability stack, and (2) illustrate how the if-then approach can be used to inform a dashboard based on observable indicators.\n                  <\/jats:p>","DOI":"10.3389\/fmicb.2026.1899413","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T05:32:25Z","timestamp":1786685545000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["From capability uplift to capability governance: an AI\u2013biosecurity stack"],"prefix":"10.3389","volume":"17","author":[{"given":"Lyly","family":"Luhachack","sequence":"first","affiliation":[{"name":"National Academies of Sciences, Engineering, and Medicine","place":["Washington, DC, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nancy","family":"Connell","sequence":"additional","affiliation":[{"name":"Department of Medicine, Rutgers New Jersey Medical School","place":["Newark, NJ, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kavita","family":"Berger","sequence":"additional","affiliation":[{"name":"National Academies of Sciences, Engineering, and Medicine","place":["Washington, DC, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,14]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1349","DOI":"10.1038\/s41586-026-10176-5","article-title":"Genome modelling and design across all domains of life with Evo 2","volume":"652","author":"Brixi","year":"2026","journal-title":"Nature"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"3856","DOI":"10.1038\/s41467-025-59231-1","article-title":"Science acceleration and accessibility with self-driving labs","volume":"16","author":"Canty","year":"2025","journal-title":"Nat. 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Open Sci."},{"key":"ref16","volume-title":"How AI Reshapes Global Preparedness for Infectious Disease","year":"2026"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1038\/s42256-025-01110-x","article-title":"Towards agentic science for advancing scientific discovery","volume":"7","author":"Xin","year":"2025","journal-title":"Nat. Mach. Intell."}],"container-title":["Frontiers in Microbiology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2026.1899413\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T05:32:26Z","timestamp":1786685546000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmicb.2026.1899413\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,14]]},"references-count":17,"alternative-id":["10.3389\/fmicb.2026.1899413"],"URL":"https:\/\/doi.org\/10.3389\/fmicb.2026.1899413","relation":{},"ISSN":["1664-302X"],"issn-type":[{"value":"1664-302X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,14]]},"article-number":"1899413"}}