AI Auto-Captions for Creators
Redesigning the caption workflow to improve speed, accuracy, and trust
2025
Captions are essential for accessibility and engagement, but the workflow is broken. While 80% of creators rely on captions to boost reach, 40% say auto-generated captions are inaccurate and frustrating. Manual captioning is slow and tedious, while fully automated captions are fast but often unreliable.
In this concept project, I explored how to redesign the caption editor to make the process feel faster, more accurate, and more trustworthy — without losing creator control.
AI Challenge
Creators want captions that are fast, accurate, and trustworthy — but these goals often compete.
🔎 Exploration
I explored different captioning workflows to evaluate trade-offs between speed, accuracy, and user control.
Full Auto was fastest but hid errors. Manual was accurate but slow. Hybrid balanced speed, accuracy, and control — making it the chosen path.
Final Design
Captions Ready
Review & Edit Captions
AI Suggestions Inline
Final Review
Impact
Removed a redundant step by combining review and edit into a single screen
Reduced friction with inline edits (AI suggestions + manual input)
Introduced clear status states to build trust in AI without slowing the flow
Applied critical thinking to balance automation with creator control
