ai-in-libraries
AI in libraries refers to the application of artificial intelligence tools—such as machine learning and natural language processing—to organize, search, and extract insights from vast collections of scientific literature and data archives. For plant science, this technology helps researchers rapidly mine botanical records, herbarium data, and published studies to uncover patterns in plant traits, evolutionary relationships, and species distributions that would be difficult to detect manually. By streamlining literature review and data discovery, AI-powered library systems accelerate the pace of botanical research and enable more comprehensive cross-referencing of historical and modern plant science findings.
open_in_new WikipediaOpenAlex · 2026-08-19
This systematic review examines how AI tools like natural language processing and knowledge graphs could help special libraries in Kenya better capture and preserve Indigenous knowledge, which is currently at risk of being lost as oral traditions fade.
Kenyan academic libraries have begun exploring AI adoption, but lack of awareness and readiness remains a significant barrier
Oral Indigenous knowledge is structurally vulnerable to loss due to its tacit, unstructured, and experiential nature
AI technologies including knowledge graphs, automated transcription, NLP, and machine learning are identified as viable tools for Indigenous knowledge preservation, though infrastructural and policy gaps persist in emerging economies