AI Agent Prevalence and Data Quality Across Multiple Online Sample Providers

This research evaluates the prevalence of AI agents and the quality of human data across various online recruitment platforms. By comparing direct panels, hybrid networks, and marketplace aggregators, the authors found that sophisticated LLM-based agents are not yet a widespread threat to most survey ecosystems. Instead, automated detections were largely concentrated on Amazon MTurk and appeared more consistent with traditional, low-quality bots than advanced AI. The study demonstrates that human respondent quality varies significantly by platform type, with first-party direct panels consistently outperforming other market segments. Ultimately, the findings suggest that structural differences in how platforms manage their respondent pools remain more critical to data integrity than the risk of AI infiltration.