This topic compares the evolution and roles of consumer conversational search engines (Perplexity, ChatGPT, Google Bard, Bing AI) and enterprise AI assistants (Microsoft 365 Copilot, IBM watsonx Assistant, Claude family, Cohere and others) as of December 2025. It covers how modern assistants balance web‑grounded answers, citation and retrieval techniques, and integration with enterprise data and workflows. Perplexity emphasizes real‑time, sourced answers and developer APIs for web‑grounded research. ChatGPT, Bard and Bing AI represent generalist conversational interfaces that differ by grounding (browsing, plugins, or search integration), multimodal capabilities, and platform tie‑ins (Edge, Chrome, cloud services). On the enterprise side, Microsoft 365 Copilot embeds assistant capabilities across productivity apps; IBM watsonx Assistant and Kore.ai focus on deployable virtual agents and multi‑agent orchestration with governance and observability; Cohere and Claude provide customizable LLM infrastructure for private models and retrieval‑augmented workflows. Notion, Harvey, PolyAI, Skit.ai and Vellum illustrate adjacent approaches — unified knowledge workspaces, domain‑specific assistants for law, voice‑first contact center agents, and prompt‑driven agent toolkits. Relevance in 2025 stems from broad production deployments: organizations require assistants that can securely access internal data, provide verifiable citations, support compliance and observability, and integrate into app ecosystems. Key trends include retrieval‑augmented generation (RAG), on‑prem/private model options, multi‑agent orchestration, voice and multimodal interfaces, and a stronger focus on governance and explainability. This comparison helps technical buyers and practitioners understand tradeoffs among accuracy, provenance, integration, customization, and governance when choosing conversational search versus enterprise assistant platforms.