Schema markup had a rough week. Google ended FAQ rich results. Four days later, Ahrefs published a report, finding that adding JSON-LD didn’t produce a clear citation lift across Google AI Overviews, AI Mode, or ChatGPT.
These developments weaken two common pitches for schema markup: increased SERP visibility and potential AI citation gains. This article examines their implications and what the data indicates about schema’s future.
Google’s Visible Schema Rewards Have Been Narrowing For Years
Google has been pulling back visible Search rewards tied to specific structured data types since 2023. Google restricted FAQ rich results to authoritative government and health sites, and HowTo rich results were limited to desktop and later deprecated.
In 2025, Google announced the retirement of several structured data features, including Course Info, Claim Review, and Estimated Salary. Book Actions was initially included but later carved out after Google removed its deprecation banner. Google called the remaining retirements “not commonly used in Search” and no longer providing value to users.
In 2026, Practice Problem structured data was deprecated. John Mueller noted on Reddit that “markup types come and go, but a precious few you should hold on to.”
The pattern is that visible structured data rewards have disappeared after becoming familiar SEO tactics. The markup itself stays valid, but the rich result doesn’t. Google doesn’t always describe these removals as responses to overuse, but the pattern offers less reason to treat any single markup type as a durable strategy.
These recent updates differ because the evidence for one proposed replacement value also weakened. The “GEO” advisory space claims schema boosts AI citations, and Ahrefs data tested part of that.
What The Ahrefs Report Found
Ahrefs tracked 1,885 web pages that added JSON-LD schema. Each page was matched against control pages that never added schema. Citation changes were measured across Google AI Overviews, AI Mode, and ChatGPT.
The results were flat. Google AI Mode showed +2.4%, ChatGPT showed +2.2%, and Google AI Overviews showed -4.6%.
The first two were too small to tell apart from random variation. The AI Overviews decline was statistically significant, but Ahrefs said it can’t confidently attribute that to schema.
Every page in the dataset already had more than 100 AI Overview citations before any schema was added. These pages were already being crawled and cited.
Ahrefs acknowledged that for pages not yet visible to AI, schema might still help with crawling, parsing, or indexing. But their data can’t confirm that.
Gianluca Fiorelli, a strategic SEO consultant, called the study “one of the more honest pieces of research to come out of the AI Search space in 2026.” But he argued the scope was narrower than the headline suggested. He compared it to “testing whether adding a label to a bottle already on the supermarket shelf makes customers pick it up more often.”
Ahrefs also cited a searchVIU experiment that found five AI systems relied on visible HTML during direct page retrieval and did not use hidden JSON-LD, Microdata, or RDFa. That finding covers one stage of the pipeline. It does not rule out schema playing a role earlier in indexing or entity understanding.
Ryan Law, Ahrefs’ director of content marketing, summarized the finding on LinkedIn, saying:
“Does adding schema markup help your pages get cited in AI search? Probably not,” he wrote. He added that schema is “probably not some magic fix for improving your AI citations.”
The Practitioner Debate
Both updates land in the middle of an active argument about schema and GEO.
Roughly 168,000 pages use the phrase “FAQ schema is critical for GEO,” according to search results that Lily Ray, VP of SEO and AI Search at Amsive, flagged on LinkedIn. She called the trend familiar.
“Anything that can be spammed in SEO, will be spammed,” Ray wrote. She’d warned about this in a 2019 Moz article when FAQ schema first launched, and described Google’s FAQ removal as the same cycle repeating.
Ray hedged throughout her post, calling it “putting on my tin foil hat” and “just an idea.” But the pattern she described is the same one visible in the timeline above. A useful markup type gets scaled as a tactic, Google pulls the reward, and the industry moves on to the next one.
Joost de Valk, founder of Yoast, made the connection explicit in a blog post. “The GEO industry is replaying early SEO, just faster,” de Valk said. “And the FAQ schema deprecation is the first concrete proof point that the cycle is back on.”
He also filed a Schema.org proposal for a new FAQSection type to address what he sees as the structural problem, separating “this page has an FAQ section” from “this page IS an FAQ.”
The frustration was sharpest from practitioners who’d been watching the GEO playbook harden around schema as its most concrete recommendation. Mark Williams-Cook, director at Candour and founder of AlsoAsked, shared the Ahrefs report on LinkedIn.
“GEO bros are selling snake oil with schema to boost citations, but people like Gianluca Fiorelli are talking sense,” he posted.
Marie Haynes, founder of Marie Haynes Consulting, commented on Ray’s post with a different theory altogether.
“My theory is that Google needed our FAQs to train AI so they gave us incentive to add them (aka rich results.) And now they don’t need them anymore,” she wrote. The theory is unconfirmed by any primary source, but it shows how far the speculation has traveled.
Some practitioners pushed back on the gloomier readings. Google’s broader guidance still presents structured data as a way to make page information machine-readable, and at a 2025 Search Central Live event in Madrid, the Search Relations team told practitioners that supported structured data types are still worth using.
What The Data Can’t Answer Yet
Whether schema helps pages that aren’t yet being cited is a separate question that the data can’t answer, because every page already had more than 100 AI Overview citations before schema was added.
The test also pooled all schema types together. Article, FAQ, Product, HowTo, and Organization were all treated as one category. Type-specific effects haven’t been isolated, and they could look different.
The 30-day measurement window may miss slower effects, and on live websites, schema changes can overlap with other page changes, making it hard to separate what schema did from what changed around it. The report only examined schema in the page’s HTML, not schema injected via JavaScript, which AI crawlers treat differently.
Ahrefs measured Google AI Overviews, AI Mode, and ChatGPT. Whether Bing, Copilot, Perplexity, Claude, or other answer systems treat schema differently from the systems Ahrefs measured is an open question.
Google’s FAQ deprecation notice says the company will continue using FAQ structured data to “better understand” pages. What that produces in measurable terms is unclear. The same uncertainty applies to whether schema affects citations indirectly, through eligibility, entity understanding, or source selection, rather than during the direct retrieval that searchVIU tested.
Nobody has published data that isolates that path.
Why This Matters
The Ahrefs data gives no measured reason to add JSON-LD, expecting short-term AI citation gains for pages already visible in AI Overviews. The trickier question is what to do with schema strategies more broadly.
Product, Review, Event, Video, and some other structured data types still support active rich result features. Organization, Person, and Article markup can still help describe entities and content, even when the payoff is less visible.
A blanket “schema doesn’t work” reading overstates what the data showed, because the test pooled all types and measured only one outcome. What the data does challenge is a specific sales pitch.
“Add schema to boost AI citations” has been one of the more concrete recommendations in GEO guides. For example, Frase.io called schema markup “critically important for AI search, GEO, and AEO.”
Without data support for that claim, it’s harder to justify the investment. AI systems in searchVIU’s test relied on visible HTML during retrieval, not JSON-LD. That suggests content structure, clear headings, and direct answers in prose may matter more for AI citation than markup structure.
Looking Ahead
The question hanging over the SEO industry is where schema creates measurable value. Adding JSON-LD didn’t measurably increase AI citations for pages already visible in AI Overviews.
For those pages, schema looks more like plumbing that serves other systems than a lever that moves citation counts. That’s still real value, but it’s a different pitch.
Featured Image: BEST-BACKGROUNDS/Shutterstock
