Information Quality Is What Wins In The AI Era
Recorded: Sept. 16, 2026, 2:40 p.m.
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Information Quality Is What Wins In The AI Era | AdExchanger
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PODCAST: AdExchanger Talks Wednesday, September 16th, 2026 – 1:30 am Bot traffic surpassed human traffic on the web for the first time in June, according to Cloudflare, which maintains a live tracker of automated versus human HTTP requests distributed to HTML content. Between then and now, the share of search requests initiated by bots increased from 57.4% to 58.6%. But letting the crawlers in isn’t a guarantee that they’ll recommend you. Frank has a phrase for it: “Information is the new bid.” For more articles featuring Tim Frank, click here. Tagged in: agentic AI // // // // // //
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In the context of the evolving artificial intelligence era, the quality of information is paramount to success, as articulated by Tim Frank, Corporate VP for monetization, commerce, and the AI economy at Microsoft. While blocking bot traffic might seem like the sole leverage for publishers, Frank suggests that allowing agents access to information is inevitable, noting that if a publisher is not available, they will not be found. This trend is underscored by data from Cloudflare, which indicates that bot traffic surpassed human traffic on the web in June, and the share of search requests initiated by bots increased from fifty-seven point four percent to fifty-eight point six percent subsequently. Frank posits that in this environment, "information is the new bid." He argues that the brands that achieve visibility in AI-driven search rankings will be those possessing the clearest, most complete, and most transparent product data, rather than those simply possessing the largest advertising budgets. Information quality is therefore critical, but Frank broadens this concept, emphasizing that it extends beyond what is explicitly present on a website. Agents aggregate information from diverse sources, weighing a brand’s own claims against external data gathered from various forums and sources, resulting in a triangulation of information that goes beyond the brand’s singular narrative. To navigate this landscape, Frank suggests that brands should actively seek to understand how AI models arrive at their recommendations. He proposes a method for this exploration: directly questioning the models in a manner similar to conducting a human focus group. By asking each model to explain its rationale for specific recommendations, brands can perform free research to assess their standing in AI search. This approach helps address the complexities introduced by agentic systems, which are constantly synthesizing and evolving their understanding of brand value from multiple inputs. |