Reddit ranks as the most-cited domain in AI-generated answers, followed by YouTube and LinkedIn, based on a new analysis of 30 million sources by Peec AI, an AI search analytics tool.

The findings. Reddit was the most-cited source across ChatGPT, Google AI Mode, Gemini, Perplexity, and AI Overviews. YouTube, LinkedIn, Wikipedia, and Forbes also ranked in the top five. Review platforms like Yelp and G2 appeared often in recommendation queries.

The research showed which domains models rely on:

• ChatGPT favored Wikipedia, Reddit, and editorial sites like Forbes.
• Google leaned toward platforms like Facebook and Yelp.
• Perplexity emphasized Reddit, LinkedIn, and G2 for B2B queries.

Why we care. To win in AI search, you need authority beyond your site. Brands that appear consistently across trusted third-party platforms are more likely to be cited.

Why these sources? AI systems prioritize perceived authority plus authentic user input:

• Reddit leads because it captures real user discussions.
• YouTube dominates video citations via transcripts and descriptions.
• Wikipedia serves as both a live source and a training dataset.

About the data. The analysis covered 30 million sources across ChatGPT, Google AI Mode, Gemini, Perplexity, and AI Overviews, measuring domains directly cited in answers to isolate what shapes responses.

The study. Top domains cited by AI search: Analysis based on 30M sources

Dig deeper. More citation research:

• AI citations favor listicles, articles, product pages (March 2026)
• Only 15% of pages retrieved by ChatGPT appear in final answers (March 2026)
• ChatGPT citations favor a small group of domains (March 2026)
• Google’s AI Mode is citing Google more than any other site (March 2026)
• 44% of ChatGPT citations come from the first third of content (February 2026)
• AI Overview fan-out rankings boost citation odds by 161% (December 2025)
• Tracking AI search citations: Who’s winning across 11 industries (October 2025)
• YouTube dominates AI search with 200x citation advantage (October 2025)
• AI search relies on brand-controlled sources, not Reddit (October 2025)
• How to get cited by AI: SEO insights from 8,000 AI citations (May 2025)
• 82% of Google AI Overviews citations come from deep pages (March 2025)

A newly published, unverified report claims Google’s Gemini AI is instructed to mirror user tone and validate emotions while grounding its responses in fact and reality.

Why we care. If accurate, AI-generated search responses may vary based on how a query is phrased — not just the information available.

What’s new. The report centers on the inherent tension in the system-level instructions guiding how Gemini responds. The report, published by Elie Berreby, head of SEO and AI search at Adorama, suggested that Gemini is instructed to:

• Match the user’s tone, energy, and intent.
• Validate emotions before responding.
• Deliver answers aligned with the user’s perspective.

What it means. The “overly supportive mandate frequently overrides the factual grounding,” Berreby wrote. So instead of acting as a neutral aggregator, AI answers may:

• Reinforce negative framing (“Why is X bad?”).
• Reinforce positive framing (“Why is X great?”).

If public perception is negative, AI may amplify it. As the report suggests:

• AI reflects existing sentiment signals.
• It doesn’t “balance” them the way blue links often do.

Query framing. The emotional framing of a query affects:

• Which sources get cited.
• How summaries are written.
• The overall tone of the answer.

Google’s AI Overviews already show tone shifts, often aligning with query intent beyond keywords. This report offers a possible explanation.

Unverified. Google hasn’t confirmed the leak. As Berreby noted in his report: “I’ve decided to share only a fraction of the leaked internal system information with the general public. I’m not sharing any sensitive data. This isn’t a zero-day exploit. This is a tiny leak.”

The report. This Gemini Leak Means You Can’t Outrank a Feeling

SEO hiring is shifting toward senior, strategy-led roles as AI reshapes search and expands the scope of the job. A new Semrush analysis of 3,900 listings shows companies now prioritize leadership, experimentation, and cross-channel visibility over pure technical execution.

Why we care. SEO hiring, career paths, and required skills are changing. Entry roles focus on execution, while most demand sits at the leadership level — owning strategy across search, AI assistants, and paid channels, with clear revenue impact.

What changed. Senior roles dominated, accounting for 59% of listings. Mid-level roles, such as specialists (15%) and managers (10%), trailed far behind.

• Companies are shifting budget toward strategy as AI tools absorb more execution work.

The skills shift. In-demand capabilities extend beyond traditional SEO into coordination, testing, and decision-making:

• Project management appeared in more than 30% of listings.
• Communication led non-senior roles at 39.4%.
• Experimentation appeared in 23.9% of senior roles compared with 14% of other roles.
• Technical SEO appeared in about 6% of listings.

Tools and channels. The SEO tech stack now spans analytics, paid media, and data.

• Google Analytics appeared in up to 47.7% of listings.
• Google Ads appeared in 29% of listings.
• SQL demand grew at the senior level.
• AI tools like ChatGPT were increasingly listed.

AI expectations: AI literacy is moving from optional to expected:

• 31% of senior roles mentioned AI.
• Nearly 10% referenced LLM familiarity.
• AI search concepts like AI search and AEO appeared more often.

Pay and positioning: SEO is increasingly treated as a business function.

• The median salary for senior roles reached $130,000, compared to $71,630 for others. Some listings were much higher.
• Degree preferences skewed toward business and marketing.

Remote work is now standard. More than 40% of listings offered remote options, with little difference by seniority.

About the data: Semrush analyzed 3,900 U.S.-based SEO job listings from Indeed as of Nov. 25. Roles were deduplicated, segmented by seniority, and analyzed using semantic keyword extraction.

The study. What 3,900 SEO Job Listings Reveal for 2026: Experiments, AI, and Six-Figure Salaries

Google removed a Search Engine Land article (Report: Clickout Media turned news sites into AI gambling hubs, published March 26) from its search results after a copyright complaint (that appears, to us, to be entirely false). Meanwhile, a similar DMCA filing led to the takedown of the original Press Gazette investigation.

What happened. A DMCA notice filed March 27 claimed Search Engine Land copied content “word for word” and used proprietary images.

• The complaint led Google to begin removing the article from search results globally.
• The notice identified the complainant as “US Webspam,” with no clear public attribution.

The context. The removed article reported that Clickout Media allegedly used expired or acquired domains to publish AI-generated gambling content.

• Press Gazette, which broke the story on March 25, said its own investigation was also removed from Google after a nearly identical complaint.
• That complaint falsely alleged infringement of a 2024 Verge article, despite no direct duplication.
• You can read their follow-up here: Press Gazette exposé of parasite SEO firm removed from Google results.

The claim details. Here’s the message we received via Google Search Console on March 27:

Description of claim: The infringing news website has blatantly and willfully violated copyright law by copying our entire content word for word, including all images, which are solely owned by our company. This includes the complete replication of our original written material, as published on our official website, along with the proprietary visuals accompanying it. Despite multiple good-faith efforts to resolve this matter amicably, the infringing party (hereinafter referred to as “Infringer”) continues to unlawfully publish and distribute our copyrighted content without permission. This is a direct and flagrant breach of our rights and a clear violation of Google’s copyright policies. We hereby demand the immediate removal of this infringing material from Google search results to protect our intellectual property.

You can read the DMCA complaint here.

What doesn’t add up. The Search Engine Land article contains no images, contradicting the complaint. Also:

• A search of its text shows no evidence of copied content.
• The notice claims “multiple good-faith efforts” to resolve the issue, but no outreach was received before filing.
• The complaint was submitted one day after publication.

What Google says. Google’s standard policy is to remove content upon receiving a valid copyright complaint, with an option for publishers to file a counter notice. The company has not commented on this specific case.

Why we care. This shows how DMCA takedowns can be weaponized to suppress reporting, including coverage of search spam and site reputation abuse. Legitimate content can be temporarily removed from search results due to unverified claims, and the resolution can take weeks or longer.

What’s next. We’ll watch whether this article is DMCA’d and removed, along with the Press Gazette’s, and anyone else covering the story.

Reactions. Here’s some reaction from X:

theholycoins isn’t owned by clickout (it’s one of the sites that would actually do negative reporting into their scams, so they probably picked one of those posts and said they were them/the original author of your dmca’d piece)

the rabbit hole on clickout goes a lot deeper than…

— (@undercover) March 30, 2026

I'm surprised this was approved by Google… I've seen them come back with rejected DMCA notices when it was clear the site was infringing copyright. This is a BS DMCA takedown that doesn't even make sense. Very interesting case… I have a feeling the article will surface again… https://t.co/Zi8hUV8g14

— Glenn Gabe (@glenngabe) March 29, 2026

A totally irrelevant site has DMCAed Search Engine Land's reporting page about ClickOut Media spamming Google's search results!

Weird enough DMCA requested was accepted by Google and now this URL https://t.co/DV8TR1NRLk from Search Engine Land isn't showing up in search… pic.twitter.com/dGbJ04KbQG

— Gagan Ghotra (@gaganghotra_) March 29, 2026

ICYMI:

Last week @pressgazette published an investigative report about a media company that acquires online publishers and exploits their domain authority for SEO shenanigans.

This is the same company that acquired a portion of @Cointelegraph to host casino & gambling content,… pic.twitter.com/duFkS7MBiP

— Afik Rechler (@kifakrec) March 29, 2026

Update, March 31. The Press Gazette and Search Engine Land articles, which were removed due to the bogus DMCA complaints, are now back in Google Search.

Reddit today opened its Pro publishing tools to all publishers, removing the waitlist and offering free access in a public beta to expand distribution and engagement.

Why we care. Reddit Pro gives you a centralized tool to track where your content spreads, streamline posting, and find the right communities. It transforms Reddit from a manual posting exercise into a structured distribution channel.

The details. You can now sign up for Reddit Pro, verify your domain (typically within three business days), and access the Links tab. With Reddit Pro, you can:

• Track where your content is shared across Reddit.
• Auto-import articles via RSS for quick posting.
• Get AI-powered recommendations on relevant communities.

Reddit also added features based on early feedback:

• Community snapshots show rules, stats, and top discussions.
• Community notes let you track strategy and context.

By the numbers. Reddit reported more than 55 billion views of publisher-related conversations in 2025. Publishers testing since September saw:

• Median post views up 46%.
• Profile views nearly doubled.
• Median comments up 48%.

What else. Reddit is expanding profile flairs to all Pro users, letting you organize posts on your profile so users can browse coverage and engage with stories.

Reddit’s announcement. Helping publishers thrive on Reddit

Google says a new compression algorithm, called TurboQuant, can compress and search massive AI data sets with near-zero indexing time, potentially removing one of the biggest speed limits in modern search systems.

What it is. TurboQuant is a way to shrink and organize the data that powers AI and search without losing accuracy. It reduces memory use while keeping results precise and cuts the time to build searchable AI indexes to “virtually zero,” according to the research paper.

How it works. Modern search converts content into vectors (lists of numbers that represent meaning). Similar ideas sit close together in this numeric space, and search finds the closest matches.

However, these vectors are large and expensive to store and search. TurboQuant addresses this by using much smaller data that behaves almost exactly like the original, through:

• Smart compression. It rotates the data mathematically to compress it cleanly, like organizing messy items into neat boxes.
• Error correction. It adds a 1-bit signal to fix small compression errors and preserve accuracy.

What it means. Vector search — the system behind semantic search and AI answers — has been slow and expensive at scale. TurboQuant makes it faster and cheaper. Google says it enables faster similarity search, lower memory costs, and real-time processing of massive datasets.

Why we care. Google can evaluate far more documents per query, not just a small subset. If/when Google adopts this in Search, AI Overviews could pull from a broader, more precise set of sources, making it easier to generate instant summaries from large data pools.

More about TurboQuant:

• Google: TurboQuant: Redefining AI efficiency with extreme compression
• Research paper (arXiv): TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
• Marie Haynes: TurboQuant has the potential to fundamentally change how Search (and AI) works

Google is testing AI-generated summaries in YouTube feeds, replacing video titles with auto-written synopses.

Some YouTube users are seeing video titles replaced by AI-generated summaries in the Android app. Reports on Reddit showed title-less video cards with collapsible summary boxes instead.

The details. Video thumbnails remain, but titles are missing in some cases.

• AI summaries appear in expandable text boxes beneath each video.
• Users must tap to expand summaries to understand the content.
• The test appears limited to YouTube on Android.

What it looks like. Here’s a screenshot Reddit user GrimmOConnor shared:

Why we care. This further abstracts creator metadata and reduces control over how your YouTube content appears. Titles remain a critical ranking and click-through signal. Replacing them with AI summaries can impact keyword targeting, brand voice, and intent matching — and increase the risk of inaccuracies that hurt performance.

The context. Google is also testing AI-generated headline rewrites in Search, extending the same approach beyond Discover and now potentially into YouTube.

• Google confirmed a “small” and “narrow” experiment replacing original page titles with AI-generated versions in Search results.
• According to Google, the goal is to better match queries and improve engagement.
• But examples showed Google shortening or rewording headlines, changing tone and meaning.

Reaction. Early feedback suggests a worse browsing experience. Expanding summaries slows discovery and adds friction to content selection, which runs counter to YouTube’s engagement goals.

What’s next. There’s no official confirmation from YouTube on a broader rollout. The missing titles may be a bug, but the AI summary feature aligns with Google’s broader push into generative AI.

First seen. We learned about this test from Android Authority.

Google is launching new Performance Max controls and reporting: audience exclusions, expanded reporting, and budget forecasting tools.

What’s new. Google announced a mix of “steering updates” and “actionable insights” for PMax:

• First-party audience exclusions: You can exclude customer lists to shift spend toward net-new customer acquisition instead of repeat conversions.
• Budget reporting: A new in-platform report projects end-of-month spend and shows how daily budget changes impact performance.
• Full audience reporting: You get detailed breakdowns by demographics, including age and gender.
• Network segmentation: You can segment placement reports by network, now under When and where ads showed.

Why we care. These updates help address concerns about PMax’s lack of control and transparency. Exclusions help you avoid wasting spend on existing customers, while improved reporting gives you clearer signals for optimization, budgeting, and brand safety decisions.

Google’s announcement. New Performance Max steering and reporting updates coming in 2026

Automated traffic grew 23.5% year over year in 2025 — about eight times faster than human traffic, which rose 3.1%, according to HUMAN Security’s State of AI Traffic report.

• AI-driven traffic appears to be a major contributor to that growth, with average monthly volume increasing 187% year over year, while traffic from AI agents and agentic browsers (e.g., OpenAI’s Atlas, Perplexity’s Comet) grew nearly 8,000% year over year.
• Automated traffic is defined in the report as: “All internet traffic generated by software systems rather than human users, including traditional automation such as search engine crawlers, monitoring bots, and conventional scraping tools, as well as AI-driven traffic.”
• This report follows Cloudflare CEO Matthew Prince’s prediction that bots could overtake human web usage by 2027.

Why we care. Search is increasingly shaped by more than human queries, crawling, and indexing. AI agents now participate in discovery, comparison, and transactions — within Google’s evolving results and across AI-driven interfaces.

The details. HUMAN groups AI-driven traffic into three broad categories:

• Training crawlers collecting data for models. They still dominate at 67.5% of AI traffic, but their share is declining as scrapers and agents scale.
• Real-time scrapers that feed AI search and answers. Scraper traffic grew nearly 600% in 2025, driven by AI-powered search and real-time answer engines.
• Agentic AI systems that execute tasks autonomously. Smaller in share, but growing fastest and most disruptive.

AI agents behave more like users. These systems aren’t limited to reading content. They increasingly navigate funnels, log in, and transact. In 2025:

• 77% of observed agent activity (requests) occurred on product and search pages.
• Nearly 9% touched account-level interactions.
• More than 2% reached checkout flows.

About the data. HUMAN analyzed more than one quadrillion interactions (requests/events) across its customer base in 2025, with aggregated, anonymized data from 2022 to 2025. It classified AI-driven traffic into training crawlers, AI scrapers, and agentic AI using user-agent strings, infrastructure signals, and observed behavior, noting limits in self-declared bot identity, which may undercount or misclassify some AI-driven activity.

Bottom line. Traffic is becoming less purely human, and discovery is no longer confined to search engines. Optimization now means deciding which machines can access, interpret, and act on your content.

The report. The 2026 State of AI Traffic & Cyberthreat Benchmark Report

Google introduced a new user agent, called Google-Agent, that signals when AI agents act on users’ behalf, marking an early shift toward agent-driven web interactions.

What happened. Google added Google-Agent to its list of user-triggered fetchers on March 20 and has begun a gradual rollout.

• The Google-Agent user agent identifies requests made by AI agents running on Google infrastructure, including experimental tools like Project Mariner.

How it works. Google-Agent appears in HTTP requests when an AI agent visits a site to complete a user-initiated task.

• Example use cases include browsing pages, evaluating content, or taking actions such as submitting forms.
• This differs from Googlebot and other crawlers, which run continuously in the background without direct user prompts.

IP ranges. Google shared the IP ranges for its desktop agent:

Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; Google-Agent; +https://developers.google.com/crawling/docs/crawlers-fetchers/google-agent) Chrome/W.X.Y.Z Safari/537.36

And the IP ranges for its mobile agent:

Mozilla/5.0 (Linux; Android 6.0.1; Nexus 5X Build/MMB29P) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/W.X.Y.Z Mobile Safari/537.36 (compatible; Google-Agent; +https://developers.google.com/crawling/docs/crawlers-fetchers/google-agent)

Why we care. This lets you identify agent-driven traffic in server logs. You can now distinguish traditional crawl activity from visits triggered by real users through AI agents. That should help you track agent-assisted conversions, understand emerging user behavior, and prepare for agentic search.

What they’re saying. According to Google’s announcement:

• “The Google-Agent user agent is rolling out over the next few weeks, and will be used by Google agents hosted on Google infrastructure to navigate the web and perform actions upon user request.”

What to watch. Early volumes will be low as the rollout continues, but now is the time to establish a baseline. What to do:

• Monitor logs for Google-Agent activity.
• Make sure CDNs and WAFs aren’t blocking the published IP ranges.
• Validate that key site actions, including forms and flows, work for automated agents.

Dig deeper. Google’s releasing Google-Agent: Here’s what to know

Visibility is no longer just about ranking. It depends on whether your content is discovered, evaluated, and selected in AI-driven search experiences.

We’re kicking off our new monthly SMX Now webinar series on April 1 at 1 p.m. ET with iPullRank’s Zach Chahalis, Patrick Schofield, and Garrett Sussman on how you must adapt.

The session introduces iPullRank’s Relevance Engineering (r19g) framework for executing Generative Engine Optimization (GEO) through an omnichannel content strategy. You’ll learn how AI search uses query fan-outs to discover and select sources, and how to structure content so it’s retrieved, surfaced, and cited.

It also emphasizes that GEO success isn’t universal. It requires testing, tailored strategies, and a three-tier measurement model spanning discovery, selection, and citation impact.

Save your spot

Search Engine Land is proud to be a media partner for iPullRank’s upcoming SEO Week event.

A company called Clickout Media is being called out for buying trusted news and niche sites, replacing them with AI-generated gambling content, and abandoning them after Google penalties. Some call this “parasite SEO,” but to me it sounds more like large-scale search spam.

What’s happening. The company acquired sports, gaming, and tech sites, then rapidly shifted them from editorial coverage to casino and crypto content, PressGazette reported.

• Sites were stripped of original reporting, filled with AI-written articles, and used to push offshore gambling links, according to former employees.

How it works. The strategy relies on buying domains with existing authority, then exploiting their ability to rank in Google. Content typically followed a pattern:

• Legitimate coverage continues briefly to preserve credibility
• Gambling content is introduced and scaled
• AI-generated articles and fake author profiles replace human writers
• Revenue comes from affiliate deals with casino operators, sometimes tied to player losses

The impact. Several previously active publications now appear deindexed, with layoffs and closures following. In some cases, even charity websites were repurposed to host gambling content.

What they’re saying. Google prohibits publishing content at scale for the primary purpose of manipulating rankings. It refers to extreme cases like this as “site reputation abuse,” a violation that can trigger manual actions and removal from Google’s index and search results.

• “While we aren’t able to comment on a specific site’s ranking on Search, our policies prohibit publishing content at scale for the primary purpose of manipulating search rankings,” Google said about this case.

Why we care. This isn’t SEO in any meaningful sense. It’s reputation abuse designed to game rankings at scale.

The report. The SEO parasites buying, exploiting and ultimately killing online newsbrands by Rob Waugh at PressGazette.

Google expanded its structured data support for forum and Q&A pages, adding properties that help you signal reply threads, quoted content, and whether content is human- or machine-generated. The update aims to reduce how Google misreads discussion and Q&A content.

What changed. Google’s QAPage docs now support commentCount and digitalSourceType. DiscussionForumPosting docs now support sharedContent plus the same commentCount and digitalSourceType.

The details. In Q&A markup, you can use commentCount on questions, answers, and comments to show total comments even if not fully marked up. answerCount + commentCount should equal total replies of any type.

How it works. digitalSourceType lets you flag whether content comes from a trained model or simpler automation. Use TrainedAlgorithmicMediaDigitalSource for LLM-style output and AlgorithmicMediaDigitalSource for simpler bots. If omitted, Google assumes human-generated content.

What’s new for forums. sharedContent lets you mark the primary item shared in a post. Google accepts WebPage, ImageObject, VideoObject, and referenced DiscussionForumPosting or Comment, including quotes or reposts.

Why we care. This gives you more precise control over how Google reads modern community content — especially forum-heavy sites, support communities, UGC platforms, and Q&A sections. Google can better distinguish answers from comments, count partial threads across pagination, and identify when a post mainly shares a link, image, video, or quoted reply.

The documentation. It was updated March 24.

AI search citations favor a small set of formats. Listicles, articles, and product pages drive over half of all mentions across major LLMs, according to new Wix Studio AI Search Lab research analyzing 75,000 AI answers and more than 1 million citations across ChatGPT, Google AI Mode, and Perplexity.

The findings. Listicles led at 21.9% of citations, followed by articles (16.7%) and product pages (13.7%). Together, these three formats made up 52% of all AI citations.

• Articles dominated informational queries, cited 2.7x more than other formats.
• Listicles captured 40% of commercial-intent citations, nearly double any other type.

Why intent wins. Query intent — not industry or model — most strongly predicts which content gets cited. This pattern held across industries, from SaaS to health.

• Informational queries skewed heavily toward articles (45.5%) and listicles (21.7%).
• Commercial queries were led by listicles (40.9%).
• Transactional and navigational queries favored product and category pages (around 40% combined).

Why we care. This research indicates that you want to map content types to user goals rather than just creating more content. Articles educate, listicles drive comparison, and product pages convert. Aligning content format with user intent could help you capture more AI citations and increase visibility.

Not all listicles perform equally. Third-party listicles accounted for 80.9% of citations in professional services, compared to 19.1% for self-promotional lists. That seems to indicate LLMs prefer neutral, editorial comparisons over brand-led rankings.

Model differences. All models favored listicles, but diverged after that.

• ChatGPT leaned heavily into articles and informational content.
• Google AI Mode showed the most balanced distribution.
• Perplexity stood out, with 17% of citations coming from discussions like Reddit and forums.

Industry patterns. Content preferences shifted slightly by vertical:

• SaaS and professional services over-indexed on listicles.
• Health favored authoritative articles.
• Ecommerce spread citations across listicles, articles, and category pages.
• Home repair showed the most even distribution across formats.

The research. The content types most cited by LLMs