Enterprise knowledge, document organization, and AI-powered productivity platforms cover the systems and workflows companies use to capture, structure, search, and act on institutional information. In 2026 this topic centers on integrating personal knowledge management (PKM) workflows, enterprise search, and real-time meeting assistants with large language models and retrieval-augmented generation (RAG) to make documents and conversations directly actionable. Key trends include embedding vector search and RAG into content stores, deploying multimodal models for richer document understanding, and balancing cloud AI services with privacy and customization needs. Representative tools illustrate these directions: Microsoft 365 Copilot brings generative assistance into Word, Excel, Teams, SharePoint and OneDrive to contextualize enterprise data; Notion provides a block-based, AI-enabled workspace for note-taking, databases, and lightweight automation; Google’s Gemini models and Vertex AI offer multimodal model capabilities and managed model lifecycle services for enterprise deployments. Claude (Anthropic) and Cohere supply conversational and customizable LLMs and embeddings for private, enterprise-tailored assistants, while IBM watsonx Assistant focuses on no-code and developer-driven virtual agents and orchestrations. Specialist utilities like ChatPDF and PDF.ai convert static documents into conversational knowledge sources for quick summaries, citations, and multi-document queries. For organizations, the practical focus is reducing search friction, preventing knowledge silos, improving meeting outcomes, and operationalizing compliance and provenance. Adoption decisions hinge on integration with existing content systems, data governance, model customization, and the ability to surface precise, auditable answers rather than generic summaries. This convergence of PKM, enterprise search, and meeting AI is maturing into pragmatic platforms that prioritize retrieval accuracy, interoperability, and enterprise controls.