AI for UX design and research — LinkedIn Learning course review

This LinkedIn Learning course covers AI applications across both the research and design phases of UX work. The instructor walks through specific tools — WireGen for Figma, Scholar GPT for research, Dovetail for user research insights, Notion AI for documentation, and Marvin for machine learning-assisted analysis — with live demonstrations.

Structure

The course is organized into four sections. AI Writing Tools covers discovery research and study preparation. AI Research Tools demonstrates Scholar GPT, Dovetail, Notion AI, and Marvin. AI Design Tools covers generative AI for social media assets and wireframing in Figma. Building AI Products introduces GPT creation and chatbot experience simulation. Each section includes screen recordings of actual tool usage.

Who it’s for

UX designers and researchers who have a LinkedIn Learning subscription (often provided through corporate learning budgets) and want practical exposure to the current AI tool ecosystem for design work. The course is beginner-friendly and does not assume prior AI experience.

Strengths

The multi-tool approach gives learners a realistic picture of the current ecosystem. Rather than promoting a single tool, the course covers the range of specialized AI tools available for different design and research tasks, helping learners make informed choices about which tools to add to their workflow.

The LinkedIn Learning format integrates with LinkedIn profiles, allowing course completion to be displayed as a professional credential. For designers seeking to signal AI competency to employers, this has practical value.

Limitations

The breadth of tools covered limits the depth of instruction on any single one. The course provides introductions rather than proficiency training. The chatbot prototyping and GPT creation sections may feel tangential for designers focused purely on visual and interaction design.