AI search agents often confirm what they already know instead of actually researching the web

May 31, 2026

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A new study suggests that leading AI search agents don't actually research on established benchmarks; they mostly use the web to confirm answers they already have. Once models have to go beyond their existing knowledge, search performance falls apart.

Frontier models like GPT-5.4, Gemini 3.1 Pro, Claude Sonnet 4.6, DeepSeek-V4-Pro, and Kimi-K2.6 keep posting higher scores on BrowseComp. The benchmark asks agents complex questions that can only be answered through multi-step browsing and piecing together information from different web sources.

Researchers from the Harbin Institute of Technology and Xiaohongshu have now shown in a study that these results say less about the agents' research skills than assumed. The authors call it "intrinsic knowledge dependence" (IKD), a reliance on internal knowledge the models absorbed during training.