Hands-on training in AI-assisted research
I work with your researchers and designers on your live projects, not practice examples. We cover using AI for transcription, coding and synthesis, checking its output against the raw data, and keeping the audit trail a regulated business needs. Your team finishes with methods they've already used once, and a way to judge new tools as they arrive.
Best for: in-house teams who already do research and want to move faster.
Where AI actually helps, and where it doesn't
A working session with your research, customer experience or design leadership. You bring your current process, tools and constraints. You leave knowing which tools are worth adopting, which to ignore, where the real time savings are, and what to watch for when customer data is sensitive. I send a written summary afterwards.
Best for: leaders asked to take a position on AI who want it to be an informed one.
You have a question. I run the study and answer it.
I handle the whole study: framing the question, recruiting participants, running interviews and usability sessions, analysis, and a findings session your team can act on that week. That can be customer experience research across the whole journey, or UX research on a specific product.
When a study needs more hands, I bring in researchers I've worked with before and stay on it with them.
Best for: a question you need answered before the next planning cycle closes.
How I use AI, and where I don't.
What AI does
- Screening and scheduling participants
- Transcription and translation
- First-pass coding across many sessions
- Finding patterns in past research nobody has time to reread
- Drafting the report from themes I've agreed
What I do
- Deciding which question is worth asking
- Designing a study that can answer it
- Running the sessions
- Judging which patterns matter
- The recommendation, and standing behind it