GenAI for Product Designers: Enhancing UX with AI

GenAI for Product Designers: Enhancing UX with AI

Instructors: Karlis Zars

Access provided by Federal University of Mato Grosso do Sul

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Evaluate where GenAI adds value in product design research, synthesis, personas, and journey mapping.
Use GenAI for usability reviews, accessibility checks, and evidence-based UX analysis with human oversight.
Apply GenAI to ideation, wireframes, UX copy, design systems, and design documentation.
Measure AI-assisted design workflows and build a responsible adoption roadmap for team rollout.

Details to know

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Assessments

2 assignments

Taught in English

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There are 2 modules in this course

This AI for UX design course gives product designers, UX researchers, and design leads a practical playbook for using generative AI in real workflows — not just prompt tricks. You'll learn AI UX research methods to synthesize interviews and support data into evidence-backed personas and journey maps, run AI-augmented usability and accessibility reviews, and use a Figma AI workflow for wireframing and rapid prototyping across SaaS, mobile, and enterprise products.

This AI product design course also covers UX copy generation, design system compliance, and AI-assisted documentation, showing you how to keep output consistent and on-brand. You'll measure AI's real impact using metrics like speed and accessibility coverage, then build a responsible 90-day adoption roadmap — through hands-on activities and a course-end project that builds lasting, measurable AI-enhanced UX skills.

This module helps learners understand where generative AI fits in modern product design work and how it can strengthen research-informed UX decisions. It introduces the main types of AI technologies relevant to designers, reviews the current tool landscape and adoption patterns, and explains how GenAI supports the product design lifecycle from discovery through iteration. Learners then move into high-impact research workflows such as synthesis, persona creation, journey mapping, heuristic evaluation, accessibility analysis, and competitor benchmarking so they can connect AI support to evidence-based design practice rather than novelty.

What's included

11 videos3 readings1 assignment1 peer review2 discussion prompts

11 videosTotal 74 minutes

Welcome and Course Goals5 minutes
Module Introduction 3 minutes
GenAI Technologies Designers Should Understand 8 minutes
The Current AI Tool Landscape for UX and Product Design 7 minutes
Where GenAI Fits in the Product Design Lifecycle 8 minutes
Finding High-Impact AI Opportunities in Design and Research Workflows 7 minutes
Synthesizing Interviews, Surveys, and Support Signals with GenAI 6 minutes
Creating Data-Backed Persona Drafts and Journey Artifacts 8 minutes
Running AI-Augmented Heuristic Evaluations 6 minutes
Benchmarking Competitor Experiences and Extracting UX Patterns 8 minutes
Bias, Privacy, and Human Judgment in AI-Assisted Research 7 minutes

3 readingsTotal 15 minutes

Welcome to the Course: Course Overview5 minutes
AI for UX: Getting Started 5 minutes
4 Ways to Use Generative AI in UX Writing 5 minutes

1 assignmentTotal 20 minutes

GenAI Foundations for UX Research and Analysis 20 minutes

1 peer reviewTotal 15 minutes

Hands-On-Learning: AI-Assisted UX Research Synthesis and Validation15 minutes

2 discussion promptsTotal 20 minutes

Finding Your Strongest AI Opportunity at Work10 minutes
Anonymization as a Daily Habit, Not a Policy10 minutes

This module focuses on how GenAI can support day-to-day product design execution and how teams can evaluate whether AI adoption is actually improving outcomes. Learners explore AI-assisted ideation, wireframe concept generation, UX copy creation, visual exploration, design system compliance, documentation, critique, and stakeholder communication. The module then turns to measurement, feedback loops, prompt refinement, team enablement, and roadmap planning so learners can introduce AI-enhanced design workflows in a structured, measurable, and responsible way.