UXPA: Using AI to Streamline Persona & Journey Map Creation

In her Using AI to Streamline Personas and Journey Map Creation talk at UXPA Boston, Kyle Soucy shared how UX researchers can effectively use AI for personas and journey maps while maintaining research integrity. Here are my notes from her talk:

Proto-personas help teams align on assumptions before research. Calling them "assumptions-based personas" helps teams understand research is still needed
For proto-personas, use documented assumptions, anecdotal evidence, and market research
Research-based personas are based on actual ethnographic research and insights from transcripts, surveys, analytics, etc.
Decide on persona sections yourself - this is the researcher's job, not AI's. every element should have a purpose and be relevant to understanding the user
Upload data to your Gen AI tool - most tools accept various file formats
Different AI tools have different security levels. Be aware of your organization's stance on data privacy
Use behavior prompts to get richer information about users, such as "When users encounter X, what do they typically do?"
For proto-personas: Ask AI to generate research questions to validate assumptions
For research-based personas: Request day-in-the-life narratives
Every element on a persona should have a purpose. If it's not helping your design team understand or empathize with users better, it doesn't belong
Researchers determine journey map elements (stages, information needed)
AI helps fill in the content based on research data
Include clear definitions of terms in your prompts (e.g., "jobs to be done")
Ask AI to label assumptions when data is incomplete to identify research gaps
Don't rely on AI for generating opportunities, this requires team effort
AI is a tool for efficiency, not a replacement for UX researchers. The only way to keep AI from taking your job is to use it to do your job better
Garbage in, garbage out - biases in your data will be amplified
AI tools hallucinate information - know your data well enough to spot inaccuracies
Don't use AI for generating opportunities or solutions - this requires team expertise