Generative Artificial Intelligence Empowers the Development of Archival Information Resources: A Study and Analysis based on Cases in Chinese Archival Sector

Abstract

Against the backdrop of digital transformation in the archival undertaking in Chinese archival sector, generative artificial intelligence (GenAI) offers a new technological pathway for the development of archival information resources. This study explores the application of GenAI in this domain, drawing upon representative cases from Chinese archival sector. It systematically analyzes the primary challenges of traditional archival development models concerning efficiency, format, and service delivery. Furthermore, it examines specific practical applications of GenAI in scenarios such as intelligent Q&A, intelligent compilation and research, archival restoration, and multimodal content creation. The research reveals how GenAI is driving transformations in archival development methodologies, service models, and the forms of outcomes. Concurrently, it identifies new challenges posed by GenAI regarding data security, technical thresholds, ethical norms, and talent development. Based on these findings, the paper proposes countermeasures and suggestions focusing on top-level design, data foundations, technical pathways, and talent cultivation, aiming to provide references for the intelligent transformation of archival institutions in China.