Qual vs. Bot: A Study So Real, It’s Artificial
The research world is buzzing about synthetic respondents, but the question remains: can AI-driven panels deliver the same nuance, insight, and emotional depth as real people? As synthetic panel technology matures, researchers are grappling with when – and if – it makes sense to replace human participation with machine-generated responses.
Join L&E Research as we unveil the results of a brand-new case study designed to put synthetic respondents to the test. In this session, we’ll compare real and AI-generated participants across several research tasks, revealing surprising insights about where synthetic data delivers, where it doesn’t, and what that means for the future of research. Along the way, we’ll highlight a few innovative platform features that made this experiment possible.
This isn’t just a theoretical discussion. We’ve built synthetic panels using retrieval-augmented generation (RAG) models and compared them to real participants recruited via Condux’s self-serve capabilities. The result? A compelling, unbiased look at when synthetic works, when it fails, and how researchers can smartly deploy it.
Whether you’re skeptical, curious, or already testing AI in your research stack, this session will help you understand what’s hype – and what’s real.
During this webinar, we’ll explore:
- What we tested: An overview of the research design, including how we structured parallel studies with synthetic and real respondents.
- How responses differed: Key findings on where synthetic participants aligned with, or diverged from, human data.
- Methodological implications: What our results suggest about the strengths and limitations of using AI-generated respondents in various research scenarios.
- Workflow considerations: A look at how survey logic, branching, and object detection influenced participant experience and outcomes.
- Practical takeaways: Where synthetic inputs can realistically support qualitative and quantitative goals, and where caution is still warranted.









