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Where does AI actually help in UX research? And where does it fall short? We broke down the research process into four stages and evaluated where AI tools add the most value today. The short version: AI is strongest at the bookends (planning and reporting) and weakest in the middle (conducting and deep analysis). š https://bit.ly/4eSlBo1 TLDR š Planning: ā Desk research, ideation, documentation. AI can help generate survey questions, draft recruitment emails, and consent forms. Conducting: ā Note-taking and structured interviews work well. But AI can't observe user behavior, read body language, or run a usability test. Tools that claim otherwise are mostly analyzing transcripts, not what users actually did. Analyzing: ā Transcription, data cleaning, and preliminary coding are solid use cases. But when it comes to making sense of qualitative data, humans are still essential. AI misses context, nuance, and contradictions. Reporting: ā This is where AI earns its keep as an editing partner. It can proofread reports, simplify UX jargon for stakeholders, and draft deliverables like personas from your research data. #AI #UXResearch #UserResearch #ResearchMethods #NNGroup
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