Next-Generation Document Intelligence: Enabling Smart Metadata, Secure Access, and Regulatory Compliance with AI

As organizations contend with expanding volumes of unstructured content and increasing regulatory pressure from frameworks such as ITAR, NARA, and federal records mandates, legacy document management systems often fail to meet the demands of intelligence, automation, and compliance. This paper introduces a next-generation Document Management System built on Microsoft SharePoint and Documentum, enhanced with artificial intelligence, natural language processing (NLP), and machine learning (ML) to automate metadata extraction, semantic document search, predictive workflow routing, and anomaly detection. By leveraging OCR and entity recognition, even scanned documents become fully searchable and classifiable, enabling a unified document intelligence pipeline. The system also incorporates adaptive security mechanisms that learn user access patterns to dynamically flag and respond to suspicious activity. Designed for regulated enterprises, the architecture embeds auto- mated classification, audit logging, and policy-based retention to meet ITAR and records compliance standards. Case studies from production deployments report a 40 percent reduction in manual handling time, improved productivity across distributed teams, and enhanced compliance readiness. This paper presents the technical architecture, AI integration strategy, and a blueprint for phased enterprise adoption of intelligent, compliant, and scalable document workflows.