AI-Powered UX Research: ChatGPT, Claude & More for Design & Discovery

Course Overview

In a world where product design is driven by data, AI is revolutionizing UX research automating repetitive tasks, generating insights, and enabling smarter decision-making. This AI-Powered UX Research Masterclass is designed to help designers, researchers, and product strategists harness the power of tools like ChatGPT, Claude, Otter, Dovetail, Perplexity, and Typeform to plan, execute, and analyze UX research efficiently.

You’ll learn how to integrate AI throughout every stage of the UX research process  from problem framing and ideation to survey design, data analysis, and insight generation. The course blends real-world examples, hands-on practice, and AI workflows to help you develop practical, job-ready research skills for the modern digital ecosystem.

Learning Objectives

By the end of this course, you will be able to:

• Understand the fundamentals and impact of AI in UX research.

• Conduct data-driven brainstorming sessions with AI frameworks.

• Design and deploy AI-assisted surveys and research forms.

• Automate interview processes, transcription, and qualitative analysis.

• Summarize and synthesize user data using ChatGPT and Dovetail.

• Perform competitive and market research using Perplexity AI.

• Deliver research-driven design recommendations with AI insights.

Detailed Course Curriculum

MODULE 1: Foundations of AI-Powered UX Research

Goal: Build a strong understanding of how AI enhances UX workflows and learn to identify opportunities for automation and insight generation.

1. Introduction to AI-Powered UX Research (4:52)

   • The evolution of UX research and how AI fits in

   • The difference between traditional and AI-augmented research

   • Overview of ChatGPT, Claude, and other AI tools for UX

2. AI Brainstorming: Solve Impossible Product Problems (10:04)

   • Leveraging AI to generate creative research hypotheses

   • Using prompt engineering for ideation

   • Real-life example: brainstorming user solutions for a mobile app

3. Use AI Frameworks to Deconstruct Any Product Problem (10:00)

   • Applying AI frameworks like “Jobs to Be Done” and “Empathy Mapping”

   • Turning product challenges into structured research questions

   • Case study: breaking down a UX challenge using ChatGPT

MODULE 2: Planning and Designing Research with AI

Goal: Learn to plan and structure UX research activities  surveys, experiments, and data collection — with the help of AI.

4. Best AI Tools for UX Research (6:11)

   • Overview of essential tools: ChatGPT, Claude, Typeform, Dovetail, Otter, Notion AI

   • Tool comparison: which platform fits which research stage

   • Integrating multiple AI tools into a single research pipeline

5. How to Plan Surveys with AI (Save Hours) (5:18)

   • AI-assisted question creation and validation

   • Ensuring unbiased and effective survey design

   • Automating distribution and follow-ups with AI

6. How to Choose the RIGHT Research Method (4:33)

   • Understanding qualitative vs. quantitative approaches

   • Using AI to recommend the best method for your project

   • Practical framework: “Method Match Matrix”

7. How to Create Surveys with Typeform and Google Forms (8:57)

   • Hands-on setup tutorial for online research tools

   • Customizing survey logic using AI-generated conditions

   • Collecting and exporting data efficiently

MODULE 3: Conducting and Analyzing User Research with AI

Goal: Use AI to streamline data gathering, summarize interviews, and derive key insights from raw data.

8. How to Setup Interviews Smarter with AI (10:06)

   • Generating discussion guides automatically

   • Using ChatGPT or Claude to personalize questions

   • Scheduling and transcription automation

9. Introduction to Summarizing Research Data (2:02)

   • How AI converts unstructured data into actionable insights

   • Example: summarizing a 30-minute interview in seconds

10. How to Analyze Survey Results with AI (8:48)

• Using AI to detect patterns, trends, and anomalies

• Creating visual insights and summaries

• Generating executive summaries from data

11. How to Upload Transcript Notes for AI Summaries (6:12)

• Preparing raw transcripts for AI processing

• Cleaning, structuring, and categorizing qualitative data

• Integration with tools like Dovetail for collaboration

MODULE 4: AI for Competitive Insights and Data-Driven Discovery

Goal: Learn to apply AI for market and competitor analysis and transform findings into strategic design insights.

12. Introduction to Otter and Dovetail (8:23)

• Managing interview data, tagging, and collaboration

• Using Dovetail’s AI insights feature to categorize user themes

• Collaborative research documentation workflow

13. How to Use Perplexity AI for Competitor Discovery (7:56)

• Finding and analyzing competitor UX strategies

• Using Perplexity AI for fast industry benchmarking

• Turning AI-generated data into actionable design opportunities

Module-by-Module Assignments

• Module 1: Brainstorm and deconstruct a real-world UX problem using ChatGPT.

• Module 2: Design an AI-generated user survey using Typeform.

• Module 3: Conduct a mock AI-assisted interview and summarize it using Dovetail.

• Module 4: Perform a competitor analysis using Perplexity AI and deliver a research insight report.

Final Capstone Project

“AI-Driven UX Research Report for a Digital Product”
Students will plan, conduct, and present a full AI-powered UX research project from defining the problem to generating AI-based insights and recommendations for improvement.

Who This Course Is For

• UX Researchers & Designers

• Product Managers & Founders

• Market Researchers

• AI Enthusiasts interested in UX

• Anyone who wants to modernize their UX research workflow

Career Outcomes

Upon completion, learners will:

• Be equipped to run AI-assisted UX research end-to-end.

• Understand how to integrate ChatGPT, Claude, Dovetail, and other AI tools in professional UX workflows.

• Build data-backed case studies for portfolios or client work.

• Gain a competitive edge in the growing field of AI-integrated UX Design.