Product Research in 2026: After the AI Pipeline

AI has changed what research operations look like. Recruiting, transcription, tagging, summarization, segmentation, even first-pass usability evaluation: most of the pipeline is now automatable, and a lot of it is already running in production. That shifts the conversation. The question is no longer "can we automate this step?" but "what are we feeding into the system, and can we trust what comes out?"

This webinar gives a structured overview of where Product, UX, and Market Research stand in 2026: what AI reliably does well, where it still fails, and why sample quality, methodology, and validation matter more than they did five years ago, not less. We'll look at automated usability evaluation, AI moderators, synthetic respondents, and auto-segmentation, and at the data quality problems that scale with them: panel fraud, AI-generated open ends, and over-recruited respondents.

For Product Managers, UX and Research leads, and Insights teams.