SERP FAQ Removal and New Data Test Schema’s AI Search Value

Schema markup has had a turbulent stretch. Google officially removed FAQ rich results from search, and just four days later, Ahrefs released a study showing that adding JSON-LD did not lead to a clear boost in citations across Google AI Overviews, AI Mode, or ChatGPT.

These two events chip away at two of the most common arguments for implementing schema: improving visibility in search results and gaining an edge in AI-powered outputs. Let’s break down what happened, what the data actually says, and what it means for the future of structured data.

Google has been steadily reducing the visible rewards for schema markup since 2023. FAQ rich results were restricted to authoritative government and health sites, and HowTo rich results were limited to desktop before being deprecated entirely. In 2025, Google retired several structured data features, including Course Info, Claim Review, and Estimated Salary. The company stated these were “not commonly used in Search” and no longer delivered value to users.

The pattern is clear: once a markup type becomes a widely used SEO tactic, Google often pulls the rich result. The markup itself remains technically valid, but the flashy SERP feature disappears. John Mueller hinted at this trend on Reddit, noting that “markup types come and go, but a precious few you should hold on to.”

What makes these latest updates different is that the evidence for another proposed benefit of schema,boosting AI citations,also took a hit. The GEO (Generative Engine Optimization) advisory space has long claimed that schema markup helps pages get cited by AI models. The Ahrefs study put that claim to the test.

Ahrefs tracked 1,885 web pages that added JSON-LD schema, comparing them against control pages that never added it. They measured citation changes across Google AI Overviews, AI Mode, and ChatGPT. The results were largely flat. AI Mode showed a +2.4% change, ChatGPT showed +2.2%, and AI Overviews actually declined by 4.6%. The first two increases were too small to be statistically significant, and while the AI Overviews decline was significant, Ahrefs could not confidently attribute it to schema.

Importantly, every page in the dataset already had more than 100 AI Overview citations before schema was added. These were already visible, crawled, and cited by AI systems. Ahrefs acknowledged that for pages not yet indexed or cited, schema might still help with crawling or parsing, but their data couldn’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.” However, he noted its scope was limited, comparing it to “testing whether adding a label to a bottle already on the supermarket shelf makes customers pick it up more often.”

Ahrefs also referenced a separate experiment by searchVIU, which found that five AI systems relied on visible HTML during direct page retrieval and did not use hidden JSON-LD, Microdata, or RDFa. That finding covers only one stage of the pipeline, but it raises questions about schema’s role in AI citation.

Ryan Law, Ahrefs’ director of content marketing, summed it up on LinkedIn: “Does adding schema markup help your pages get cited in AI search? Probably not.” He added that schema is “probably not some magic fix for improving your AI citations.”

The practitioner response has been heated. Lily Ray, VP of SEO and AI Search at Amsive, flagged on LinkedIn that roughly 168,000 pages use the phrase “FAQ schema is critical for GEO.” She called the trend predictable, writing, “Anything that can be spammed in SEO, will be spammed.” She pointed back to her 2019 Moz article warning about FAQ schema overuse, noting that Google’s removal is simply the same cycle repeating.

Joost de Valk, founder of Yoast, made the connection explicit in a blog post: “The GEO industry is replaying early SEO, just faster. 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 separate “this page has an FAQ section” from “this page IS an FAQ.”

Mark Williams-Cook, director at Candour, shared the Ahrefs report on LinkedIn with a blunt take: “GEO bros are selling snake oil with schema to boost citations, but people like Gianluca Fiorelli are talking sense.”

Marie Haynes, founder of Marie Haynes Consulting, offered a different theory on Ray’s post: “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.” While unconfirmed, the theory reflects how far speculation has run.

The data has clear gaps. The Ahrefs study pooled all schema types together,Article, FAQ, Product, HowTo, and Organization were treated as one category. Type-specific effects remain untested. The 30-day measurement window may miss slower impacts, and schema changes on live websites often overlap with other page updates. The test only examined schema in the page’s HTML, not JavaScript-injected schema, which AI crawlers handle differently. And the study only measured Google AI Overviews, AI Mode, and ChatGPT, leaving Bing, Copilot, Perplexity, and Claude unexamined.

Google’s FAQ deprecation notice says the company will continue using FAQ structured data to “better understand” pages. What that means in measurable terms is unclear. Whether schema affects citations indirectly,through entity understanding or source selection,remains an open question that no published data has yet isolated.

So why does this matter? The Ahrefs data provides no measurable reason to add JSON-LD expecting short-term AI citation gains for pages already visible in AI Overviews. The harder question is what to do with schema strategies more broadly.

Product, Review, Event, Video, and 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.” That claim has been one of the most concrete recommendations in GEO guides. For example, Frase.io called schema markup “critically important for AI search, GEO, and AEO.” Without data support, that investment is harder to justify.

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. For pages already visible in AI Overviews, adding JSON-LD did not measurably increase citations. Schema may still serve as important plumbing for other systems, but it no longer looks like a lever that moves citation counts. That’s still real value, but it’s a very different pitch.