Google Workspace AI Research
Berkeley Innovation × Google Workspace Collaboration
A consulting project for Google Workspace that aimed to create understanding on the pain points and usages of AI in college students’ workflows. A comprehensive user research project that investigated how AI improves learning, collaboration, and communication workflows. Delivered actionable product insights and feature recommendations for Google Workspace.
Research Methodology
- Over twenty 1 hr student interviews over a wide variety of majors and perspectives.
- Secondary research and surveys
- Project walkthroughs and focus groups
- Comprehensive synthesis and analysis
Key Insights
- Primary use cases for AI include a feeling of being on a time crunch, exploring personal interests, and building a foundation
- Concerns range from technical (prompting), to ethical and social when using AI
- Students want nuanced control and context-aware AI
- Integration between tools is crucial for workflow success
User Archetypes
- AI Advocate: High frequency, high trust users
- Reluctant Reliant: Low frequency, high trust users
- Active Avoidant: High frequency, low trust users
- DIY-Devotee: Low frequency, low trust users
Journey Mapping
- Essay and writing workflows
- Technical project management
- Scheduling and planning processes
- Collaboration and communication flows
Product Recommendations
- Gmail: Inbox summaries, affinity tagging, project profiles
- Drive: Group project structure, workspace cohesion
- Docs: Research sourcing assistant, smart study suggestions
- * Other insights can't be shared due to NDA
