A conversation that
follows the answer.

Build the research process around the conversation.

We are evaluating conversational agents as part of an AI-assisted research workflow. The goal is to explore whether guided conversations can give participants more flexibility while still producing useful, contextual accounts of their experience.

This approach is in development. The suitability of an AI-led session depends on the topic, audience, study design, and the capabilities of the selected technology.

What we are exploring

• Voice and video sessions with natural turn-taking.
• Follow-up questions that respond to a participant’s answer.
• Consistent study introductions and task explanations.
• Transcript capture and evidence organization for review.

What needs a careful check

Latency, interruptions, leading questions, and off-topic responses can change the participant experience. We evaluate these alongside session controls, recording choices, data handling, and integration requirements.

Participants should understand when they are interacting with AI, what is recorded, and how to pause or leave. A pilot needs a clear approach to problems the agent cannot handle.

Keep interpretation connected to people.

AI can propose themes and organize material. Research conclusions should be reviewed against real participant evidence. Generated personas or simulated responses do not establish what actual users think or need.