
This workshop explores the evolution and integration of Artificial Intelligence within Document Management Systems (DMS), tracing its development from legacy optical character recognition (OCR) to contemporary cognitive automation. We analyze the historical trajectory of AI through phases of technological enhancement, specifically focusing on the transition from static archival storage to intelligent, context-aware information ecosystems. The session identifies cutting-edge features currently transforming the DMS landscape, including Large Language Model (LLM) integration for automated metadata extraction, semantic search capabilities, and predictive classification. By examining the synergy between AI and document lifecycles, this presentation demonstrates how these advancements optimize discoverability, ensure regulatory compliance, and redefine organizational knowledge management in the digital era.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
