AI in UX Research - PDF Workbook + Notion Template Toolkit
AI is already replacing researchers who don’t know how to work with it. Learn how AI is reshaping UX research and build the judgement, boundaries, and credibility needed to stay employable.
“AI can already summarise interviews, cluster insights, and generate research output at scale. Teams that don’t know how to use it responsibly are being quietly deprioritised or replaced. This toolkit teaches you how to work with AI in UX research without losing rigour, relevance, or your role.”This 160+ page PDF workbook + interactive Notion template toolkit helps you design AI-supported research workflows you can defend at a time when organisations are questioning which research roles still add value.✨ What’s inside:
📘 PDF Workbook – Understand how AI actually works in UX research, where it helps, where it fails, and where human judgement must stay in control
🛠 10+ Ready-to-Use Notion Templates – Design AI-supported research workflows, audits, and decision frameworks you can reuse across projects
🗒️ 7+ Practical Exercises – Apply AI intentionally to real research tasks, not hypothetical examples
🔍 AI Risk & Bias Audit Tools – Identify blind spots, missing voices, and over-confidence before insights turn into decisions
🎯 Research Workflow Frameworks – Integrate AI into planning, synthesis, and reporting without automating judgement
📋 Checklists & Cheat Sheets – Fast reference guides to avoid misuse, false confidence, and “the AI said so” thinking
🖇 Editable Workbook Pages in Notion – Move seamlessly between thinking, documenting, and doing all in one place
Most AI content stops at tools or prompts. This one focuses on decisions, boundaries, and accountability. It doesn’t teach you how to automate research it teaches you how to use AI without breaking research. This book is not about:
❌ AI prompts, hacks, or “magic” workflows
❌ Tool reviews, feature comparisons, or software tutorials
❌ Replacing researchers with automation
❌ Speed-at-all-costs research or insight shortcuts
❌ Letting AI decide what users need
❌ Treating AI output as truth or final insight
❌ Building AI products or training models
❌ Technical implementation, coding, or data science
❌ “The AI said so” decision-making
❌ Chasing trends without accountability
If you’re being asked to use AI to speed up research, summarise interviews, cluster insights, or support decisions and you’re unsure what’s safe, what’s risky, or how to explain it, this workbook is for you. It’s built for UX researchers, designers, and product teams who need clear guidance on how to integrate AI into real research tasks without over-claiming, introducing bias, or losing ownership of decisions. If you want practical templates, checklists, and workflows you can use immediately to work with AI and confidently defend your approach to stakeholders, this workbook was made for you.