ChatGPT Traffic Rose 48% as Bing Fell 50% in US Data, Exposing an SEO Measurement Gap

ChatGPT.com reached about 1.09 billion monthly US visits in July 2026, a 48.38% year-over-year increase, according to Semrush Traffic Analytics data. In the same comparison, Bing.com traffic fell about 50.43%. The contrast does not show AI replacing conventional search overnight. Google and YouTube still led the US dataset by a wide margin. It does show that the places where people first discover information are changing, while many website analytics setups remain poorly equipped to show the full effect. The July 2026 snapshot puts ChatGPT ninth among the leading US sites measured by Semrush. Businesses that still view organic discovery mainly through Google rankings and familiar referral reports risk missing a growing part of the customer journey: a user may ask an AI assistant for options, follow a recommendation, and arrive on a website without a cleanly identifiable source in Google Analytics 4. The underlying Semrush US Trending Websites data compares July 2026 traffic with July 2025. It is a view of US web traffic in Semrush's ranked-site dataset, not a count of every search or AI interaction. Still, the scale of the movement makes AI-assisted discovery a practical measurement issue, not simply a trend to monitor. What the traffic shift means for SEO measurement The key implication is not that businesses should abandon established search channels. Google recorded roughly 25.31 billion monthly US visits in the July snapshot, while YouTube recorded about 10.27 billion. Those figures underline how large the established platforms remain. What has changed is the need to distinguish where discovery happens from the source that ultimately appears in analytics. ChatGPT's growth can create new paths to content, products and services. But referral details may be unavailable when users move from an AI interface to a website, particularly when the originating referrer is stripped. In GA4, those visits can be grouped as Direct or remain otherwise difficult to classify. Web