Agents
Conversational AI
Conversational AI is a category of AI systems designed to conduct natural-language dialogues with humans — including chatbots, virtual assistants, and voice interfaces. Modern conversational AI uses large language models to understand intent, maintain dialogue context, and generate coherent multi-turn responses.
Conversational AI spans a wide capability range: rule-based chatbots handle narrow FAQ tasks with decision trees; LLM-powered assistants handle open-domain questions with context and nuance; agentic conversational systems combine LLMs with tool use to take actions on the user's behalf. For enterprises, the key design decision is where on this spectrum a use case sits — most customer-service deployments benefit from constrained, retrieval-grounded conversational AI rather than open-ended generation.
Related terms
- AI Agent — An AI agent is a software system that takes a goal, plans a sequence of steps to reach it, executes those steps using tools (APIs, databases, browsers, code), and adapts when steps fail.
- Agentic AI — Agentic AI describes systems that pursue goals autonomously over multiple steps without per-step human approval.
- RAG (Retrieval-Augmented Generation) — RAG is a pattern in which an AI model retrieves relevant documents from a knowledge base at query time and uses them as additional context to generate its response.
- LLM (Large Language Model) — A large language model (LLM) is a neural network trained on broad text corpora that can generate, summarize, translate, classify, and reason about natural language.