AI & Machine Learning

Conversational AI

Conversational AI is technology that lets people interact with software in natural language, by text or voice, through chatbots and virtual assistants that understand requests, keep track of context and respond or act.

Earlier systems relied on intent classification, entity extraction and scripted dialogue flows. Modern assistants are typically built on large language models, combined with retrieval-augmented generation for knowledge, function calling for actions, and speech recognition and text-to-speech for voice. A dialogue manager or agent framework keeps track of conversation state and decides when to hand over to a person.

Uses include customer support, IT and HR help desks, booking and order tracking, internal knowledge assistants, and voice interfaces for field and shop-floor staff who need hands-free access to procedures or machine information. Multilingual capability matters in diverse workforces.

Quality depends on grounding answers in approved sources, handling ambiguity, recognising when to escalate and protecting personal data. Where regulations such as the EU AI Act require it, people must be informed that they are interacting with an AI system. Metrics include resolution rate, escalation rate, answer accuracy and user satisfaction.

Key points

• Natural-language interaction with software by text or voice
• Modern assistants combine LLMs, RAG, tools and speech technology
• Escalation to a person must be designed in
• The EU AI Act requires disclosure of AI interaction in many cases

Related terms

• Large Language Model (LLM)AI & Machine Learning
• Retrieval-Augmented Generation (RAG)AI & Machine Learning
• Automatic Speech Recognition (ASR)AI & Machine Learning
• Text-to-Speech (Speech Synthesis)AI & Machine Learning
• AI AgentAI & Machine Learning
• Natural Language Processing (NLP)AI & Machine Learning

Terms that refer to Conversational AI

• Vector DatabaseAI & Machine Learning