Build UI-level mechanisms that let users manage or override automation based upon user goals, context scenarios or system failure states.
No system can anticipate all user contexts. Controls give users agency and keep trust intact even when the AI gets it wrong.
How to use this pattern
Use progressive disclosure: Start with minimal automation and allow users to opt into more complex or autonomous features over time.
E.g., Canva Magic Studio starts with simple AI suggestions like text or image generation then gradually reveals advanced tools like Magic Write, AI video scenes and brand voice customisation.
Give users automation controls: UI controls like toggles, sliders, or rule-based settings to let users choose when and how automation can be controlled. E.g., Gmail lets users disable Smart Compose.
Design for automation error recovery: Give users correction when AI fails (false positives/negatives). Add manual override, undo, or escalate options to human support. E.g., GitHub Copilot suggests code inline, but developers can easily reject, modify or undo suggestions when output is off.