Google's AI Search Spam Policies: What's Allowed and What Gets You Penalized (2026)

What Actually Changed on May 15, 2026

On May 15, 2026 (UTC), Google updated its Search spam policies. The change is small in word count and large in implication. The policies now clarify that the rules also apply to efforts aimed at influencing AI-generated answers in Search, meaning the content that appears in AI Overviews and the responses generated in AI Mode. For anyone who had been treating AI surfaces as an unregulated frontier, the update closes that loophole in a single sentence.

The most important thing to understand is what did not change. This update does not introduce new rules. It applies existing ones to a new set of surfaces. Every prohibition that already governed traditional rankings now governs attempts to manipulate AI answers as well. Google did not invent a separate rulebook for generative search. It pointed at the rulebook it already had and said the obvious thing out loud: these rules cover this too.

That framing matters because a cottage industry had already started to form around the idea that AI citations were a fresh growth hack, free of the constraints that govern links and rankings. The May update removes any ambiguity. If you were waiting for Google to tell you whether buying your way into AI answers was acceptable, the answer is no, and it was always no. The policy simply caught up to the way people had started talking about the opportunity.

How Google Now Defines Spam

Under the updated policies, Google's definition of spam includes two parallel ideas. The first is attempting to manipulate Search systems into ranking content highly. The second is attempting to manipulate generative AI responses in Google Search. Both sit inside the same definition. There is no carve-out that says a tactic aimed at an AI Overview gets gentler treatment than the same tactic aimed at a blue link.

This two-part definition is the structural change worth internalizing. For years, spam policy was framed almost entirely around rankings, because rankings were the only prize. Now the prize has two forms. A page can win a traditional position, or it can win a citation inside an AI-generated answer. Google's response is to treat manipulation of either outcome as the same offense. The intent to deceive or manipulate is what triggers the policy, not the specific pixel where the manipulation would have paid off.

For practitioners, this collapses a distinction that some had hoped to exploit. The argument that "we are not trying to rank, we are just trying to get cited" does not survive the updated definition. Trying to get cited through manipulation is now named explicitly as spam. If your strategy for AI visibility relies on tricking the system rather than earning trust, the policy now describes your strategy directly. For the legitimate side of this work, our overview of generative engine optimization lays out the version that stays inside the lines.

The Prohibited Categories That Now Cover AI Answers

Google named specific practices in the update, and the list will look familiar to anyone who has read the spam policies before. Prohibited practices include keyword stuffing, link spam, machine-generated traffic, malware, misleading functionality, and scaled content abuse. None of these are new categories. What is new is the explicit confirmation that each one applies whether the goal is a high ranking or a citation in an AI Overview.

The links and citations category is the one that catches the most people off guard, so it deserves a direct quote of the principle. Buying or selling links for ranking purposes, excessive link exchanges, and using automated services to create links are violations regardless of whether the goal is traditional rankings or AI Overview citations. Read that twice if you sell or buy links. The escape hatch some had imagined, where link schemes become acceptable as long as you frame them as AI optimization, does not exist.

Keyword stuffing is worth a separate note because it has quietly resurfaced under a new name. Some "AI optimization" advice encourages cramming pages with question-and-answer blocks and repeated entity mentions in the hope of triggering AI citations. Past a point of genuine usefulness, that is keyword stuffing with extra steps, and it sits inside the named prohibitions. The fact that you are stuffing for an AI answer instead of a ranking does not move it outside the policy.

Why Buying Citations Is a Trap

A specific kind of service has appeared in the wake of AI search: vendors promising to get your brand cited in AI Overviews and chatbot answers, often through some combination of paid placements, link building, and content syndication at scale. The pitch is seductive because AI citations feel new and unclaimed. The reality is that the mechanics underneath most of these offers are the same link and content schemes Google has prohibited for years, repackaged with an AI label.

The May update makes the risk explicit. When buying or selling links for ranking purposes, excessive link exchanges, and automated link creation are violations regardless of the goal, a service that builds links to manufacture AI citations is selling you a policy violation. You are not buying a clever new tactic. You are buying exposure to the same penalties that have always followed link schemes, with the added problem that the practice is now named in the context you are using it.

There is also a practical reason these services rarely deliver lasting results. AI systems decide what to cite based on signals of authority, clarity, and trust that are difficult to fake at scale. A burst of purchased links or syndicated content might create a brief blip, but it does not build the durable authority that makes a source the obvious one to cite. You end up carrying the policy risk without the reward. Our breakdown of how citation optimization works across ChatGPT, Perplexity, and Google covers what actually earns a mention, and none of it involves a checkout page.

Scaled Content Abuse and AI-Generated Content

Scaled content abuse is the named category most likely to catch otherwise well-meaning teams, because the tools to commit it are now cheap and easy. The policy targets producing large volumes of content primarily to manipulate Search systems, with little original value to users. The key words are primarily to manipulate and little original value. A model writing the text is not the violation. Mass-producing low-value pages to game the system is the violation, whoever or whatever drafts them.

This is the distinction that trips people up. AI-generated content is not prohibited. Plenty of useful, accurate, genuinely helpful content is drafted with AI assistance and ranks and gets cited without issue. The policy does not care about the tool. It cares about value and intent. If you use a model to help write a thorough, accurate, original piece that serves readers, you are fine. If you point a model at a keyword list and publish ten thousand thin pages to flood the index, you are inside scaled content abuse, and the AI label does not protect you.

The temptation is real precisely because production is now nearly free. When generating a thousand pages costs almost nothing, the instinct is to generate a thousand pages. That instinct is the trap. The pages that earn rankings and citations are the ones with distinct, useful content, real data, and a reason to exist beyond hitting a query. Volume without value is exactly what the scaled content abuse policy exists to catch. We go deeper on the boundary in our piece on AI content detection and Google penalties, which separates the safe uses from the ones that draw a flag.

Site Reputation Is Part of the Calculation

Spam policy does not operate page by page in isolation. The overall reputation of a site shapes how its content is treated, and that becomes especially relevant once AI answers enter the picture. AI systems lean heavily on signals of trust when deciding what to surface and cite, which means a site that accumulates spam violations is not just risking individual pages. It is eroding the reputation that makes the whole domain a candidate for citation in the first place.

This is why a few aggressive shortcuts can do more damage than they appear to. A handful of purchased links or a batch of thin AI-generated pages might seem like a small bet against a big upside. But if those tactics dent the site's standing, the cost is not contained to the pages involved. It can suppress the visibility of your genuinely good content too, including the pages you would most want an AI Overview to cite. The downside is correlated across the whole site in a way that makes the gamble worse than it looks.

The constructive read is that reputation compounds in the other direction as well. A site that consistently publishes accurate, well-structured, genuinely useful content builds the kind of standing that makes citation the default outcome rather than something you chase. That is slower than buying placements, and it is the only version that holds up. If you want a clear-eyed assessment of where your site stands, our SEO audit looks at exactly these reputation and quality signals before they become a problem.

The One Principle to Carry Forward

If you remember nothing else from the May update, remember the core principle underneath it. If a tactic would be deceptive, manipulative, or low value in traditional Search, do not assume it becomes acceptable because the target surface is an AI-generated response. That single sentence resolves almost every edge case you will encounter. You do not need to memorize a separate set of AI rules. You need to apply the judgment you already have to a new surface.

This principle is useful because it is a test you can run before you act, without waiting for a policy update to name your specific tactic. Ask whether the thing you are about to do would be considered manipulation if the goal were a ranking. If the answer is yes, the AI framing does not save it. If the answer is no, because the tactic is genuinely about making your content clearer, more authoritative, and easier to trust, then it is the legitimate work of optimization regardless of which surface it targets.

The principle also clears up a confusion that has muddied a lot of AI search advice. There is a real and important difference between optimizing your content so AI systems can understand and trust it, which is encouraged, and manipulating those systems into citing content that does not deserve it, which is prohibited. Both get called "AI optimization" in casual conversation. The policy draws the line where it has always been drawn, between earning a result and gaming one. Our look at the SEO myths that refuse to die covers several tactics that fail this exact test.

How to Earn AI Citations the Safe Way

The work that earns AI citations safely is not mysterious, and it is not new. It is the same set of fundamentals that earns rankings, applied with awareness of how AI systems parse content. Start with real expertise. AI answers tend to pull from sources that demonstrate genuine, first-hand knowledge of a topic, with specific detail rather than generic summary. If your content reads like it was assembled from other people's content, it gives an AI system little reason to prefer you as a source.

Cite your sources and make your claims verifiable. AI systems are increasingly attentive to whether a page backs its assertions, because a model that cites you is staking its own answer on your accuracy. Clear sourcing, accurate data, and claims that hold up under scrutiny make your content safer to cite. Pair that with clean structure: clear headings, direct answers near the questions they address, and content organized so a machine can extract the relevant passage without guessing.

Structured data does real work here too. Valid schema markup tells AI systems what your content is and what it claims, which makes it easier to parse and to trust. This is allowed, encouraged, and unrelated to any manipulation concern, because it describes your content honestly rather than gaming a system. Our guide to structured data for AI search covers the markup that matters, and our schema markup generator produces valid JSON-LD you can drop into your templates. The throughline across all of this is genuine authority. You build it, you do not buy it, and it is the only foundation for AI visibility that the spam policies will never threaten.

Where We Stand on This

We will be direct about how we operate, because this update validates a stance we have held from the start. We do not buy citations, we do not run link schemes, and we do not guarantee rankings or AI placements. Those promises are either dishonest or dangerous, and usually both. The May update confirms that the tactics behind such guarantees are policy violations regardless of whether they target rankings or AI answers. We would rather tell you the truth about how this works than sell you a shortcut that puts your site at risk.

The honest version of this work is also the more durable one. Earning AI visibility through real expertise, accurate content, clear structure, and valid schema is slower than buying placements, and it is the version that survives the next policy update, the next algorithm change, and the next wave of cheap manipulation services. Every piece of authority you build the right way keeps paying out. Every shortcut you take adds a liability that compounds against you the moment the site's reputation takes a hit.

If you want AI search visibility built on the work that actually lasts, that is exactly what our AIO optimization service is designed to deliver. We optimize your content so AI systems can understand, trust, and cite it, without a single tactic that the spam policies would flag. If you are not sure where your site stands today, start with a conversation about your goals through our optimization consultation, and we will tell you the truth about what we see.

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