Conversational UI
What is Conversational UI?
Conversational UI is an AI design pattern where users interact with systems through natural language, either via text or voice, just like talking to another person. Instead of learning complex menus and buttons, you simply type or speak what you need and the AI understands your intent. It's perfect for customer support chatbots, voice assistants in cars or smart homes, or any application where natural language is faster than clicking. Examples include Siri understanding your voice commands, Slack AI responding in team conversations, or ChatGPT engaging in back-and-forth dialogue to solve complex problems.
Problem
Traditional interfaces are rigid, requiring users to learn specific patterns. Users prefer natural language but struggle with AI lacking context or nuance.
Solution
Create conversational interfaces that understand natural language, maintain context, and respond naturally. Design for text and voice with appropriate personality and tone.
Real-World Examples
Implementation
AI Design Prompt
Guidelines & Considerations
Implementation Guidelines
Use natural language; avoid overly formal or robotic responses.
Maintain conversation context and reference previous interactions.
Provide clear conversation starters and example prompts.
Handle misunderstandings gracefully with clarifying questions.
Use appropriate personality and tone matching your brand.
Support both structured commands and free-form natural language.
Provide visual cues for conversation state (typing indicators, read receipts).
Design for both synchronous and asynchronous conversation patterns.
Include conversation history and search functionality.
Handle interruptions and topic changes smoothly.
Design Considerations
Balance personality with professionalism based on use case.
Consider cultural differences in communication styles.
Plan for multilingual support and language detection.
Design appropriate fallback mechanisms when AI doesn't understand.
Consider privacy implications of conversation history storage.
Account for accessibility needs in text and voice interfaces.
Plan for conversation handoffs between AI and human agents.
Consider the cognitive load of extended conversations.
Design appropriate boundaries for AI personality and capabilities.
Test with diverse user groups to validate conversational patterns.