The AI Visibility Report tracks what changes across ChatGPT, Perplexity, Google AI Overviews, and the models behind them every two weeks, then translates it into what it means for brands that want to show up when a customer asks an AI for a recommendation. This fortnight the through-line is measurement. Here is what moved.
Google put AI visibility numbers inside Search Console. The new Search Generative AI performance reports show how often your pages appeared in AI Overviews, AI Mode, and Discover, cut by impressions, pages, countries, devices, and dates. There is no click data yet, and the rollout starts with a subset of UK sites, a requirement of the UK competition regulator, before any wider expansion. A separate toggle keeps your content out of those AI features and leaves your normal ranking untouched.
Bing already reports something Google does not: Citation Share, your slice of all citations for a grounding query. Between the two engines you now have first-party windows into AI visibility, thin but real, and both belong in the same review as the rest of your search data.
ChatGPT cites a different set of brands depending on how hard it thinks. A Semrush study with Kevin Indig ran 100 prompts across 20 buyer journeys and found only 25.6 percent of cited domains overlapped between its fast answers and its deep-reasoning answers. Citation rate climbed from 50 to 68 percent, sources per answer rose from 2.6 to 4.5, and government and academic sources jumped from 1.9 to 8.8 percent while Reddit's share fell. You can win the quick answer and disappear from the considered one.
The cleanest content angle this fortnight: original data you own is the citation asset a competitor cannot copy. A rival can borrow your framing, but not the numbers you measured yourself. The catch is structure. Data buried in a chart image or behind rendering does not get cited. Written as a clean, self-contained sentence with a clear claim, it does.
On llms.txt, the picture hardened rather than changed. Google Search ignores the file, an Ahrefs study of 137,000 sites found 97 percent of them got zero crawler requests, and the item Google actually weights in its own agent-readiness check is WebMCP, the protocol for an agent to operate a page. Watch that, not the text file.
Google is the headline, and this time it is a product, not a policy note. On June 3 Google announced Search Generative AI performance reports in Search Console, with separate views for Search and for Discover. They show how often URLs from your site appeared inside generative AI features, broken out by impressions, pages, countries, devices, and dates, at daily, weekly, and monthly granularity. Two limits matter. There is no click data in this first version, so you can see that an assistant surfaced your page but not whether anyone came through, and Google has not dated the release that adds clicks. The rollout is deliberately narrow, starting with a subset of UK site owners before any wider expansion. The UK-first order is not a coincidence: the UK Competition and Markets Authority is requiring Google to give UK publishers this reporting and an opt-out control, and Google began honoring the content-blocking toggle on June 17. A separate toggle lets you keep your content out of grounding those AI features, and opting out does not change your standard organic rankings. The plain read, which Search Engine Journal put well, is that Google filed AI visibility under Search on purpose. Treat it as one more line in your Search Console review, not a separate report nobody opens.
Bing has quietly held the lead on first-party AI reporting since February and extended it in June. Its AI Performance report in Bing Webmaster Tools now carries four views: Intents, Topics, Citation Share, and Compare. Citation Share is the one to note, because it reports your percentage of all citations for a grounding query rather than a raw count, which is the closest thing to a share-of-voice figure any engine ships today. It covers Bing and Copilot grounding, not ChatGPT or Google, so it is one window, not the whole room.
Two smaller vendor moves point the same direction. Apple's WebKit team shipped a Safari MCP server that lets an AI agent debug a site for SEO and Core Web Vitals, early and developer-facing, but another sign that browser vendors are building the plumbing for agents to read and operate pages directly. And the measurement shelf keeps filling: Rank Math launched an AI visibility tracker, joining HubSpot, Ahrefs Brand Radar, Semrush, and a long tail of smaller tools. None of these is a citation mechanism. The signal is that the tracking layer for AI search is becoming a commodity, which raises the bar for anyone whose offer is only a dashboard.
Further out, agentic commerce moved from demo to distribution. Sea and OpenAI put the Shopee marketplace inside ChatGPT across eight Southeast Asian markets plus Brazil, and are testing OpenAI's Operator agent to complete purchases end to end. If your buyers shop in those regions this is live already; for everyone else it is a preview. Once an assistant can finish a purchase, your product data and third-party reputation carry more weight than your storefront design.
The most useful data this fortnight is the Semrush and Kevin Indig study on ChatGPT reasoning modes. They tested 100 prompts across 20 buyer journeys in B2B SaaS, finance, consumer tech, and health, comparing minimal reasoning against high reasoning. Only 25.6 percent of cited domains overlapped, so nearly three in four sources changed when ChatGPT shifted from a fast answer to a thinking one. Citation rate rose from 50 to 68 percent and cited answers pulled more sources, from 2.6 to 4.5 each. The mix shifted with the depth: Reddit fell from 15 to 7 percent, user-generated and review content dropped from 14.3 to 6 percent, and government and academic sources climbed from 1.9 to 8.8 percent. The lesson is that a one-shot citation check misleads. Whether you appear depends on how deeply the model reasons, and the deep path leans on documentation and primary sources over forums and reviews.
The llms.txt story did not change so much as sharpen. Chrome's Lighthouse promoted its Agentic Browsing audit to default in May, and that audit checks whether an llms.txt file exists. Google Search still ignores the file and its June guidance confirms no ranking effect. These are two different Google teams with two different jobs, and the timing overlap is what made it look like an endorsement. The crawl data keeps pointing the same way: an Ahrefs analysis of 137,000 sites found 97 percent of llms.txt files got zero crawler requests. The item Google actually weights inside that agent-readiness audit is WebMCP, the Web Model Context Protocol for an agent to operate a page. If you want to read ahead of the field, read up on WebMCP, and keep llms.txt as a cheap, low-confidence item, never a lever.
The stronger content angle came from Search Engine Land: original data you own is the most defensible citation asset, because a competitor can copy your framing but not your numbers. Structure decides whether an engine can lift it. A figure locked in a chart image or shown only after rendering does not get cited. The same figure written as a clean sentence with a clear claim does. If you run studies, surveys, or hold benchmark data from your own operations, that is your best shot at a citation nobody can take from you.
One rule has not moved and still fails the most audits: the major US assistants read raw HTML and do not run client-side JavaScript. Content that only appears after rendering is at risk of being invisible to ChatGPT, Claude, and Perplexity. If you want a page cited, serve its content as server-side rendered or static HTML.
The practitioner conversation kept circling one question: whether GEO and AEO are real disciplines or SEO with a new label. The clearest thread ran in r/seogrowth at 51 comments, where the experienced crowd landed where it usually does: search optimization gets you ranked, answer-engine work gets you cited, and the two sit closer together than the guru framing admits because AI visibility rides on a solid search base. r/aeo carried the same debate. Running underneath it was a cluster of summer traffic-drop threads across the SEO subreddits, people watching clicks fall and asking whether it is a Google shift, an AI shift, or the usual July slump. The honest answer in those threads was usually all three at once.
Among the people worth following, Lily Ray kept making the case that classic Google standing and AI visibility are linked, arguing that a manual action measurably cuts your citations in AI Overviews and ChatGPT, and that you can rank in Google and still have your brand left out of the AI recommendation. Glenn Gabe warned that sites flattened by earlier 2026 updates keep flatlining and that trying to game GEO is the wrong response. The framing from this group this fortnight was mood and caution more than any new tactic.
Start with measurement, because two engines just made it easier. Pull Bing's Citation Share into your next visibility review as a baseline you can move over time, and if you own UK sites, check whether the new Search Console AI reports have reached you. Both are impressions and share, not clicks or attribution, so treat them as monitoring baselines rather than proof of traffic. The point is that you no longer have to guess entirely from third-party trackers.
Stop trusting a single citation check. The reasoning-mode study shows the answer to “are we cited?” flips depending on how hard the model thinks, so test your visibility across fast and deep answers and over time, not once. Because the deep path rewards documentation and primary sources, the content that holds up is thorough and well-structured, not thin and keyword-shaped.
If you want a citation a competitor cannot copy, publish data you measured yourself. A benchmark from your own operations, a survey of your customers, a number nobody else holds, written as a clear sentence an engine can lift. That is worth more than any llms.txt or schema tactic on offer right now.
One caution on the advice going around that LinkedIn is the second most cited source in AI search. That number is a cross-industry average weighted toward business and professional questions. For B2B and professional queries LinkedIn does rank at or near the top, and there the tactic is worth knowing: Perplexity tends to cite company pages while ChatGPT and Google AI Mode tend to cite individual member profiles, so a brand that only posts from its company page leaves citations on the table. For a consumer brand the cited sources skew to video, forums, and product or category pages, with LinkedIn far lower. Before you act on any “top cited domains” list, check which sources actually get cited for your category. The ranking is a starting prior, not a universal fact.
And keep half an eye on WebMCP. The browser vendors are all moving toward agents that read and operate pages directly, and that is the surface likely to matter next. There is nothing to ship today, but it is the right thing to start understanding now.
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