The Japanese category strategy firm suswork published category research data comparing how brands are chosen through AI recommendation with how they are chosen through human recall, using cafes and toothpaste as the examples. The article says AI recommendation now matters alongside recall in everyday buying scenes. Marketers should track AI recommendation as a goal separate from brand recall and check which products an assistant names in their own category.
Research from MIT and Stanford points to a risk that AI agents will find the cheapest route to whatever target an SEO team sets, according to Search Engine Journal. The column says teams need metrics that agents cannot fake. Marketers should set AI visibility targets that require real demand, such as sales, rather than counts an agent can produce.
Meta has opened its personal agent Muse to outside developers and introduced Connectors, a mechanism that lets a third-party service be called mid-conversation when a user asks Muse for something, so a service no longer depends on the user searching for it. The article works through an analysis by researcher and podcast host Greg Isenberg, who compares the shift to Apple opening the App Store in 2008 and uses equipment rental as an example of a service pulled in partway through a planning conversation. Marketers should look for the points in a customer's request chain where their service could be the one the agent calls, rather than assuming the customer will search for them.
Muse, Meta's personal AI agent, is topping app store charts and adding users quickly, and Meta is promoting the agent across its own apps and beyond, TechCrunch reports. Amazon blocked Muse from buying on its marketplace this month because the agent does not see Amazon's ads. Marketers should treat Meta's agent as a growing product discovery surface and check that their product data can be read and recommended inside it.
OMR asked German marketers about their first ChatGPT Ads campaigns and says they report good click rates alongside disappointing tests; OMR also put questions to OpenAI. The piece covers what the format delivers for advertisers in Germany, where the ads have been sold since late August 2026. Marketers planning ChatGPT Ads tests should read these results as early benchmarks for click rates and conversion before committing budget.
CINC updated the prompt generator in AIsearchmap, its GEO and LLMO tool for tracking how AI answer engines mention brands. The tool now builds monitoring prompts from a site's own information, suggesting axes such as main topic, comparison, target and area for users to adjust. Marketers using AIsearchmap should expect to set up answer-engine visibility tracking with less manual prompt design, while teams evaluating GEO tools get another feature to compare.
Google announced a new query fan-out framework called R4T-Diffusion, which Search Engine Journal describes as ready for production-scale search. Query fan-out is the step where one submitted question is split into several sub-queries before an answer is assembled. Marketers should watch how Google describes the rollout, because that split decides which pages are eligible to be cited in Google's AI answers.
Google has deployed a system called SAFE that catches AI-generated content spam, and Search Engine Journal says the rollout may be part of Google's September 2026 spam update. The outlet reports the system is already live rather than planned. Marketers publishing machine-written pages at scale should expect those pages to be re-evaluated in Google's index, since pages that drop out of the index cannot be drawn into AI Overviews or AI Mode answers.
Google updated its VideoObject structured data documentation to support creator and author properties and to clarify which interaction types interactionStatistic covers. The change affects the video markup Google reads from a page. Marketers who publish video can add the creator property and review their interactionStatistic values so their pages stay aligned with what Google documents.