Human-AI Collaboration

Contextual Assistance

Offer timely, proactive help and suggestions based on user context, history, and needs.

What is Contextual Assistance?

Contextual Assistance is an AI design pattern where systems proactively offer help based on user context and behavior, without waiting to be asked. Instead of interrupting workflows with generic tips, this pattern analyzes what users are doing right now and suggests relevant actions at the perfect moment. It's most effective for repetitive tasks, complex applications, and situations where AI can learn from patterns to predict needs. Examples include Gmail's Smart Compose finishing your sentences, search autocomplete guessing your query, and Notion suggesting relevant pages as you type.

Problem

Users need guidance but often don't know what or when to ask. Traditional help interrupts workflows.

Solution

Design intelligent assistance that proactively offers relevant help, suggestions, or information based on user context and behavior. Anticipate needs rather than waiting for explicit requests.

Real-World Examples

Implementation

Figma Make Prompt

Guidelines & Considerations

Implementation Guidelines

1

Make assistance subtle and non-intrusive; don't interrupt the user's flow

2

Provide clear indications that suggestions are AI-generated

3

Allow users to easily accept, modify, or dismiss suggestions

4

Gradually improve suggestions based on user feedback and acceptance patterns

5

Offer ways to access more detailed help when contextual assistance isn't sufficient

Design Considerations

1

Balance between proactive help and avoiding unnecessary interruptions

2

Consider privacy implications of analyzing user behavior to provide contextual help

3

Ensure the system doesn't make assumptions that could frustrate users if incorrect

4

Provide transparency about why certain suggestions are being made

5

Include settings to adjust the frequency and type of assistance

Related Patterns

Related Guides