AI for UX Research
September 23
9:00a - 5:00p ET
Location TBD
Llewyn Paine
Strategy Consultant
About this workshop
AI is rapidly changing how teams conduct UX research–but most practitioners still lack a reliable way to determine where AI improves business outcomes and where it introduces too much risk.
In this workshop, you'll use transparent, custom-built AI research tools to observe exactly how AI impacts research data and business decisions. Through hands-on experimentation, grounded in academic research and controlled testing, you'll gain an accurate understanding of AI's capabilities and failure modes for common research approaches.
You'll leave with a framework for evaluating AI research tools and evidence-based best practices for making informed trade-offs between AI and traditional methods.
Target Audience
People who conduct UX research (user researchers, market researchers, designers, product managers, etc.)
Pre-requisites
Familiarity with fundamental UX research methods (interviews, usability tests, surveys, qualitative data analysis) No prior familiarity with AI is assumed. All tools will be provided.
Takeaways
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Learn evidence-based best practices for applying AI in UX research
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Understand how common AI research tools work at a technical level, and how this impacts your data
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Apply a framework to evaluate AI capabilities in the context of UX research, even as the tools change
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Get hands-on experience with the technology, working directly with the latest models and AI agents that major commercial research tools are built on
High-Level Agenda
DAY 1
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Warm-up: AI + UXR hopes and concerns
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Approaching UXR as Jobs To Be Done for stakeholders
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Introduce a framework for thinking about AI augmentation of UXR
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Understand the “main jobs” of UXR
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Large Language Model (LLM) foundations for UXR
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Why you should understand LLMs even if you’re using commercial AI tools
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Review LLM fundamentals
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Practice and evaluate: LLMs for qualitative analysis
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Introduce key considerations when using LLMs for qualitative analysis
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Practice qualitative analysis with a long-context LLM
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Discuss how to optimize for stakeholder needs
DAY 2
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Practice and evaluate: AI-moderated interviewing
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Introduce AI moderation tool
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Practice creating and participating in an AI-moderated interview
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Review evidence-based best practices
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Test a web interface with an AI agent
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Discuss the emergence of agents in the context of UXR JTBD
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Introduce “Agent Experience”
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Practice conducting a usability test for an AI agent
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Extending the framework to other AI UXR tools (time permitting)
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Introduce AI tools and trends not previously discussed
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Create your own AI validation plan using the JTBD framework
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Wrap-up
Instructor