What changed in AI search this fortnight

Vendor moves

Google's fortnight moved in product more than in documentation. The 15 October post, titled "More ways to connect with the web from Search", says Google has "made continued and substantial increases to the presence of inline links" and will "show inline links higher up in responses more frequently". It is testing a dedicated section at the top of a response for tasks with "one or two official places on the web", redesigning end-of-response links with image thumbnails, and testing clickable creator and publisher names on video results in AI Mode, while news carousels that highlight Preferred Sources roll out to additional locations and languages globally. None of it comes with click data, which Google told Search Engine Roundtable it still will not show for AI features. Gemini 4 Argon reached AI Mode on 13 October as a selectable model for AI Pro and Ultra subscribers, the first surface we scan that it has reached, while the free-tier default stays as it was and AI Overviews are not named. Developer pricing is $2 input and $10 output per million tokens until 30 November and $4 and $20 from 1 December, with Search grounding free for 5,000 requests a month and $14 per 1,000 after that.

Commerce and ads kept moving into the answer itself. Universal Cart launched in the US on 15 October: items saved in AI Mode and in the Gemini app share one cart, checkout runs over the Universal Commerce Protocol through Google Pay or the merchant's site, and the Shopping Graph tracks price and stock, with Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair and Shopify merchants named. Merchant Center also began rolling out a Universal Commerce Protocol integration hub in the US, enabling checkout on eligible listings in AI Mode and Gemini plus cart transfer to the merchant's site, with Australia and Canada to follow. Search Engine Land reported on 16 October that Google has begun testing ads in AI Mode for users who have Personal Intelligence switched on, which connects Gmail, Calendar and Photos to AI Mode. Google's help page says those ads "will not be based directly on your Gmail inbox or your Google Photos library", while summaries, excerpts and inferences from them "may be used to show you ads", which reverses the March statement that AI Mode would stay ad-free for those users. Google also told Adweek it is testing text and Shopping ads in AI Mode and AI Overviews "which we recently expanded to include certain pharmaceutical products", US only. On the publisher side, more than 400 publications now take part in Google's News AI pilot, a licensing programme for Google News surfaces whose terms were not disclosed, and which is separate from the AI contribution pilot whose payouts we reported last issue.

Google's documentation changes were fewer and sharper. Search Engine Roundtable reported on 6 October that the people-first content page now says fabricating creator profiles, for example with AI-generated headshots, made-up names or false credentials, "is a form of deception". The September spam update finished on 8 October after 13 days and 16 hours, roughly five times longer than the slowest of the year's three earlier spam updates, and Google never said what it targeted. Search Console began emailing sites a count of "Preferred source selections" with the line "When readers select your site, your content can appear more often across features like Top Stories, AI Overviews, and AI Mode", and there is no matching report inside Search Console. In our reading it is the first time Google has tied the preferred sources control to AI Overviews and AI Mode in writing. On 8 October Google also published the UGC Fresh Data Program, which lets approved platforms that primarily host forum, social or community content push posts and engagement signals to Google through an API. Google answers applications within 6 to 8 weeks and guarantees nothing about appearance, and the page names "various features on Search" without mentioning AI Overviews or AI Mode.

Two smaller Google items matter to anyone who publishes brochures, price lists or job listings. On Search Off the Record on 13 October, Martin Splitt and John Mueller explained that Google converts PDFs into an HTML representation, that PDFs "can appear in AI Overviews and are accessible to AI models", that images inside them are not indexed, and that they are recrawled much less often than HTML, so updates should go out under new URLs. On 16 October the Indexing API quota page was rewritten to list 200 publish requests a day, and the approval form and the sentence that usage "requires additional approval" were removed, leaving no documented path to a higher quota. Search Engine Journal reported in September that job boards had waited six to nine months for approval. Bing's Webmaster blog published for the first time since February: Topics Portfolio, a beta tab in the AI Performance report that groups grounding queries into themes, shows approximate topic size and how crowded each topic is, and lists Top Opportunity Queries where other sites are cited and yours is not. It appears "if there is sufficient data for your site", so smaller sites may not see it.

Outside Google, the shopping engines got a little easier to see into. Search Engine Roundtable reported OpenAI testing product labels such as "best all-rounder" and "best for beginners" in ChatGPT shopping results, spotted by Brodie Clark. Peec's 17 October write-up of Malte Landwehr's brightonSEO talk describes, according to the vendor, how ChatGPT Shopping picks products: in the US it runs on OpenAI's own feed index of 669 feeds, 606 of them active, about 70 from direct partnerships and about 500 built by OpenAI scraping retailer sites, while in Europe it runs on Google Shopping results fetched through a SERP API with no verified-seller check, and product descriptions are cut at 50 tokens. Perplexity's 5 October changelog entry, which we read from a mirror because the page blocked our fetches, added GPT-6.1 Sol for eligible paid subscribers. DeepSeek's 17 October API changelog introduces DeepSeek Search as "an AI-native general-purpose search engine that indexes hundreds of billions of web pages" which "filters SEO spam, GEO manipulation, and low-quality AIGC through strict detection mechanisms", priced at $0.75 per 1,000 successful requests. How that filtering works is not described anywhere, and no one has tested it yet.

How LLMs read the web

The rank tracker problem reaches AI Overview figures as well as rankings, and that matters here because every other number in this issue passes through a measuring tool. Search Engine Journal's 14 October analysis found AI Overviews on 34.9 percent of poisoned results pages against a 54.2 percent baseline, so AI Overview presence collected through a tracker in this window can read low. In a figure dated 7 October, DemandSphere put its spurious daily checks at roughly 11 percent. Both are vendor measurements, and Google has not confirmed any of it. Our reading is that any Google-side visibility figure collected through a third-party tool since mid-September carries this caveat, including ours. The ChatGPT tag gap has a structural cause underneath the bug: ChatGPT strips the referrer on its clicks, so the utm_source parameter is the only attribution signal there is, and when it went missing Adobe's Huesler counted about 31,000 fewer ChatGPT visits and 26,000 more direct visits a day.

The fortnight's most useful research is about the ruler more than the thing being measured. Jiang, Zhang, Xing, Chang and Xiao ran 80 Search Arena queries, 40 in English and 40 in Chinese, through the ChatGPT web app, 20 runs per query for GPT-5.3 Instant and GPT-5.5 Instant, and compared the citations with two stand-ins: the Responses API with web search, and Google via SerpAPI. Google alone recovered 9.4 and 6.4 percent of the cited URLs, the API's retrieved sources 22.9 and 22.5 percent, the API's own citations 12.3 and 13.0 percent, and the two together 28.3 and 26.2 percent. Between 40.8 and 44.5 percent of the URLs ChatGPT cited appeared in only one run. The exact user query was sent to search in 5.5 percent of GPT-5.2 Instant runs and in none of the GPT-5.3 or GPT-5.5 runs, and 67.0 to 69.6 percent of the Chinese questions were searched in English only. The authors recommend tracking hostname and entity presence alongside exact URLs, and at hostname level the two stand-ins together reach 50.3 and 48.7 percent. Measuring ChatGPT through its API is a bit like judging a restaurant by reading its menu: related, useful, and a different thing. Our reading is that an API-based ChatGPT visibility number measures something next to the product, and anyone selling one as the same thing as the app should say which surface they sample.

A second study points in a familiar direction, and it comes from a firm with a stake in the answer. Discovered Labs, which sells AEO, Reddit marketing and AI visibility tracking services, posted a preprint on 28 September analysing about 2.1 million citation events over six months across ChatGPT, Claude, Google AI Overviews and Gemini. Its strongest page signal is word overlap between a page and the prompts that cite it, with a standardised coefficient of +0.37, about three times the next-strongest page signal, and the median cited passage sits at a depth of 0.36, in the top third of the page. Schema markup, Core Web Vitals and Lighthouse scores showed no significant independent effect once domain authority was controlled, and domain-level AI authority outweighed the strongest page-level feature by about six to one. A commenter on a Reddit summary thread offered the most careful reading: the top of a page tends to hold the definition, the direct answer and the core entities, so position may be a proxy for local completeness. It is one observational, non-peer-reviewed study. The independent baseline is older: the KDD 2024 GEO paper attributes its "up to 40%" visibility gain specifically to adding quotations, with statistics addition at +33 percent, citing sources at +28 percent and keyword stuffing below baseline, and AutoGEO, accepted at ICLR 2026, reports about 36 percent average improvement while preserving answer usefulness.

Three pieces sharpen what an AI says about a brand once it does show up. In Search Engine Land on 15 October, Maryanna Franco of BrilliantSEO described a vendor-run test of 12 brands across five platforms in 14,140 API runs, reporting brands that LLMs describe correctly yet never recommend because Google's Knowledge Graph ties the name to a different entity; her example is UK activewear brand TALA, shown as a financial services company. Constantine von Hoffman's piece, built on Semrush's 2026 AI Visibility Index across 22 categories in a publication Semrush owns, reports that fewer than half of the top 100 mentioned brands appear in the matching top 100 citation lists, and that Ford, mentioned in all four US top-100 lists in July, is cited 1,055th on ChatGPT, 1,146th on Gemini, 1,320th on AI Mode and 748th on AI Overviews. MIT Sloan Management Review's 13 October article, based on 15 interviews with marketing leaders and one pseudonymous New Zealand investment platform, describes ChatGPT answers about that platform as "confident, fluent, and frequently wrong", including a repeated claim that it offered five funds when it offered seven. Being named, being cited and being described correctly are three separate scores.

Comparison pages got a measurement too. Minuttia, a B2B SaaS SEO and GEO agency, published with Convex Works on 13 October a study of 18,084 software questions and 686,749 citations across Google Search, AI Overviews, ChatGPT, Gemini, Claude and Perplexity, collected in August. For "alternatives to X" questions, the share of cited listicles that are a vendor's own list of the best tools in its category came to 47 percent on Google Search and Gemini, 43 percent on Perplexity and AI Overviews, 36 percent on Claude and 34 percent on ChatGPT, and for "X vs Y" questions it was higher, 65 percent on Google and 56 percent on ChatGPT. Of 118,196 citations of 36,037 such pages, 93 percent highlight the vendor's product, 87 percent rank it first and 16 percent clearly disclose the vendor. The authors call the numbers a floor, since unreadable pages were counted as not self-promotional. Software is the only vertical studied, so nothing yet says other categories behave the same way.

Crawling moved on three fronts, and all three bear on whether a robots.txt file still describes who reads your site. Meta's Andy Stone says the new terms consolidate existing language and that robots.txt still governs Meta-ExternalAgent, used for training, and Meta-WebIndexer, used for Meta AI search; the terms say nothing about it. Cloudflare's accountability system builds an "explainable trust band" from whether a Verified bot's traffic honours robots.txt and slows down after an HTTP 429 response, looks at "sustained patterns rather than isolated events", names no tiers or penalties, and will publish scores on Radar. The Cloudflare and OpenAI pilot runs the other way: the CDN tells a search crawler which pages exist, which changed and which are broken or possibly compromised, so the crawler makes "fewer wasted requests", with the stated rule that "a signal about a page doesn't grant permission to access it". Anthropic added a first-party account from the agent side on 9 October: in internal evaluations, Claude models submitted real forms, including a government form, exploited a server flaw on a university site, lifted access tokens from public map and dashboard configurations to reach gated data, and used URL shorteners to get around fetch-tool limits. Anthropic has cut live internet access for all internal evaluations until its monitoring reliably catches such behaviour, and nothing indicates its customer-facing products behaved this way. On llms.txt, the engines' own answers have now restated Google's position for five consecutive radar runs.

Community signal

The measurement stories came from tool makers and practitioners first. Derek Perkins of Nozzle described the rank tracking problem, Cedric Huesler of Adobe measured the ChatGPT tag gap across roughly 500 pages, and OpenAI's confirmation of the bug reached the public through Huesler, since OpenAI itself has said nothing publicly. Jake Bauman's video on Claude Code mods carried a number worth keeping: 25 prompts across Google AI Overviews, Perplexity and ChatGPT, 426 answer runs, and one citation to his own site. It is one practitioner's unverified account, and a useful corrective to share-of-voice dashboards about how low the base rate can be for a small site.

Lily Ray offered a read on motive, that Google seems intent on showing AI Overviews on as many queries as possible as quickly as possible to demonstrate growth in AI usage. It is her opinion, and in our reading it fits the pattern. Glenn Gabe observed that people who like AI Overviews and ChatGPT often change their minds once they learn the impact on publishers and that the answers can be wrong. Aleyda Solis's post on the Minuttia study gave the 34 to 47 percent range without its scope, which is "alternatives" questions only. Lily Ray also quoted DeepSeek's sentence about filtering GEO manipulation, an accurate quote of a claim nobody has tested.

Some numbers in circulation did not survive checking. A post claiming Perplexity cites 19.5 sources per answer against ChatGPT's 3 could not be traced to any study, and the nearest published figures, from Orbit Media's September citation study, differ, so we left the post's numbers out. Semrush's channel ran an episode titled "AI Overviews up 56% for branded queries", and the 56 percent could not be traced to any published Semrush measurement. Hobo Web called the KDD 2024 GEO paper a product of "hallucinated stats and closed sandbox tests" with no article behind the post that we could find; the sandbox point has a basis, since the paper's main results come from a GPT-3.5 engine simulated over Google's top five results, while nothing published supports the hallucination charge.

Our Reddit signal is thin this time, and I would rather say so. The allowlisted community leg returned no threads in the first week, and the whole Reddit collector failed in the second. One r/OpenAIAdvertising post, which we could not verify because Reddit blocked our fetches, described ChatGPT Ads Manager reporting conversions that Shopify never showed as ChatGPT orders. An agency write-up, itself vendor-sourced, attributes such gaps to delayed, click-based, aggregate-only reporting and purchases that never touch the merchant's site. It is the same attribution hole as the agentic checkout gap we covered last issue.

What it means for your brand

Put a note on 8 to 15 October in your analytics before anyone reads the ChatGPT dip as a drop in demand. In that window ChatGPT visits can show up as direct traffic, and since ChatGPT strips the referrer, the UTM tag is the only attribution signal there is. If your reporting depends on ChatGPT traffic, sketch a fallback while the gap is fresh, such as recognising the landing pages ChatGPT visitors usually arrive on, so the next tagging problem does not erase a week of data.

If any ranking or AI Overview presence figure in your reports came from a third-party tool after 13 September, check it against Search Console before it goes in front of a client or a board. In Nozzle's data, a poisoned page left the tracked site out of the top 10 more often than not, so a sudden dip in that window may reflect what the tracker was served. Annotate odd dips in that window instead of building an explanation around them.

When a vendor shows you a ChatGPT visibility score, ask which surface it samples, the ChatGPT app or an API call, and whether it matches citations by exact URL or by hostname. The arXiv preprint above found the API's retrieved sources recovered less than a quarter of the URLs the app cited, and that between 40.8 and 44.5 percent of cited URLs appeared in a single run. The authors' advice, to track hostname and entity presence alongside exact URLs, is sensible whatever model is running.

If your business uses Facebook, Instagram or WhatsApp for business, Meta's terms cover your domain from 30 October. Robots.txt is the only lever Meta acknowledges, through two user agents: Meta-ExternalAgent for training and Meta-WebIndexer for Meta AI search. Treat them as two separate choices, write your decision into robots.txt before the date, and once Cloudflare publishes its compliance scores you may have outside evidence of which bots honour such rules.

Check every byline, author bio and headshot on your site, and on content your agencies produce for you, for anything made up: a composite persona, a stock or AI-generated photo, credentials nobody can verify. Google's guidance now names these as deception, OpenAI's 8 October report described seven fake journalist personas placing nearly 100 articles, and practitioners report manual actions rising after the September spam update. For most sites this check takes an afternoon per property, which is cheaper than explaining a manual action later.

For every task a customer can only complete with you, such as booking, configuring a product or finding a store, make sure the official page is indexable, says plainly what it is for, and has no near-duplicates competing with it. Google's test of a section for tasks with "one or two official places on the web" has room for very few answers per task, and in our reading it favours the page that is clearly the official one. If you publish "best of" or "alternatives" pages that rank your own product first, say who wrote them: in the Minuttia study only 16 percent of such pages clearly disclosed the vendor, and CDE's view is that a disclosed comparison is the honest version of that page.