--- title: "Google Just Made Grounding Official: What It Means for the Future of Organic Traffic" description: "A site's E-E-A-T, and the author's, is now non-negotiable. We've fully entered the era of entities." date: 2026-06-29T00:00:00.000Z --- The recent report **"A Pragmatic Approach to AI Governance in America,"** published by Google in June 2026, isn't just a policy document. For anyone working in digital content, SEO, or brand positioning, it's a roadmap for how Generative Engine Optimization (GEO) is going to operate from here on out. But before we get into the practical implications, let's break down what the document actually says, in plain language. * * * ## What is this document, and why does it matter? Google published this report to propose a balanced approach to AI regulation in the United States. The core argument is that the current debate is stuck in a false dichotomy: either regulate too much and kill innovation, or don't regulate at all and let the risks run loose. Google's proposal is a middle path: regulate frontier AI (the big models like Gemini, GPT, Claude) through an independent body overseen by the federal government, called **FARO** (Frontier AI Regulatory Organization) in the document, and, for AI that's already part of everyday life (chatbots, assistants, generative search tools), adapt existing laws instead of building new regulation from scratch. The document covers topics like protecting minors, copyright, privacy, energy infrastructure, and information integrity. But there's one section that changes the game for the digital content market. * * * ## The three pillars that directly affect content creators ### 1. Training AI on web data is fair use, and now it's confirmed Google states explicitly in the document that **using publicly available internet data to train AI models is a transformative use**, protected under fair use principles in the US and equivalent exceptions in other countries. The analogy used is a sharp one: it's like an art student visiting a gallery for inspiration. The student isn't copying the works, they're absorbing patterns, styles, and references to create something new. In practice, this means **LLMs are going to keep training on web content**, regardless of new regulation. The conversation about blocking AI crawlers, then, isn't about stopping training, it's about positioning strategy. * * * ### 2. Robots.txt is still in your hands, but blocking has a strategic cost The document notes that site owners retain **control over whether their content is used to develop models**, through simple directives like `Google-Extended` in the `robots.txt` file. That sounds like a win for content creators. And it is, partly. The problem is that [blocking AI crawlers](/en/blog/como-bloquear-treinamento-de-ia-sem-sumir-do-google-a-mudanca-que-a-cloudflare-fez-em-julho-de-2026/) today is effectively **choosing not to appear in the new discovery journeys**. When someone asks a question to Google AI Overviews, Perplexity, ChatGPT Search, or any generative search engine, those systems need sources to ground their answers in. Blocked sources are ignored sources. The real strategic question isn't "can I block it?" It's "is it worth blocking and disappearing from AI-generated answers?" * * * ### 3. Grounding is the new currency of digital visibility This is the most relevant point in the document for anyone working in content. Google confirms it's **exploring partnerships and value-exchange models** with sites whose content actively contributes to the _factuality_ and _freshness_ of generative answers, what the document calls **grounding**. What is [grounding](https://ai.google.dev/gemini-api/docs/google-search)? It's the process by which a language model "anchors" its answer to real, verifiable data, instead of generating information from scratch (and potentially hallucinating). The model needs reliable, up-to-date, coherent sources to make sure what it says is true. In simple terms: **LLMs need sites like yours so they don't lie**. And Google is officially exploring ways to pay for that. This represents a fundamental shift in optimization logic: | Before (classic SEO) | Now (GEO) | |---|---| | Index keywords | Provide factual layers | | Rank pages | Get cited in answers | | Attract clicks | Be the source the AI uses | | Appear in SERPs | Ground generative answers | * * * ## The consequence nobody's talking about: E-E-A-T became a technical factor If grounding is the new currency, then **the credibility of the entity behind the content is the new infrastructure**. [E-E-A-T](https://developers.google.com/search/docs/fundamentals/creating-helpful-content), short for **Experience, Expertise, Authoritativeness, and Trustworthiness**, has stopped being a subjective editorial quality criterion and become, in practice, the filter LLMs use to decide whether content deserves to be cited or ignored. It's the same principle behind [topical authority clusters](/en/blog/autoridade-topica-clusters-de-conteudo-seo-geo/). Here's the reasoning: Language models don't just evaluate the text on a single, isolated page. They map the consistency of the entity behind that content across the entire web: on the blog, on LinkedIn, on third-party outlets, in mentions, interviews, and academic or commercial publications. If what you say on your blog contradicts what's on your LinkedIn profile, or if your positioning shifts depending on context, **the AI fails to pin down your identity**. And what the AI can't clearly identify, it simply won't use as a source. * * * ## What counts as an "entity" in the context of AI? An entity, in this context, is anything the AI can identify consistently and unambiguously: a person, a company, a brand, a concept. Google's Knowledge Graph, for example, runs on entities, the same kind of structured data that underpins [schema.org applied to service businesses](/en/blog/o-poder-do-schema-org-para-empresas-de-servicos-um-guia-completo-para-o-seo-local/). When AI looks for an expert on a given topic, it's not searching for keywords, it's searching for **coherent patterns that confirm who this person or brand is and what their area of authority is**. For AI, consistency equals trustworthiness. And trustworthiness is the selection criterion for grounding. **Practical examples:** - A company that writes about "marketing automation" on its blog, but whose founder talks about completely different topics on LinkedIn: inconsistent signal, less eligible for grounding. - A consultant with published articles on industry outlets, a LinkedIn profile aligned with their site's topic, and mentions in podcasts and case studies: clear entity, more eligible for grounding. * * * ## Information consistency has become a technical ranking factor This is the most direct conclusion you can draw from Google's document, cross-referenced with how language models actually work today: **The consistency of your information across the web is, officially, the new technical ranking factor.** This isn't about having the same text copy-pasted in multiple places. It's about having a coherent, recognizable, verifiable positioning: - The same area of authority reinforced across multiple channels. - Company data (name, location, area of operation) consistent across directories, social media, and third-party sites. - Content that's kept up to date and reflects the current state of knowledge in the field. - Proprietary primary sources: studies, data, exclusive perspectives no other site has. Whoever isn't the established grounding source for their niche will simply be ignored by generative engines. * * * ## What to do starting now If you produce content, run a brand, or work in SEO and digital marketing, here are the priorities: **Build your identity as an entity.** Make sure your name or your brand's name appears consistently and coherently across every channel: website, LinkedIn, Google Business Profile, industry directories, third-party mentions. **Produce content with primary data.** AI favors sources that have information that doesn't exist anywhere else. Original research, exclusive data, opinions grounded in real experience carry far more weight than articles that just rehash what already exists. **Update your content regularly.** Grounding depends on freshness. Outdated content is a hallucination risk for AI, and it learns to avoid unreliable sources. **Don't block AI crawlers without a clear strategy.** If your monetization depends on visibility and discovery, blocking AI access to your content is the wrong move. If your business model is selling exclusive access to content, that's a different conversation, and Google itself suggests licensing models are being explored. **Invest in E-E-A-T as infrastructure, not as content.** Writing well isn't enough. The AI needs to be able to clearly identify who you are, what you stand for, and why you're a trustworthy source on your topic. That's entity positioning work, not just content production. * * * ## Conclusion Google's document wasn't written for SEO professionals. But it contains, between the lines, the clearest confirmation yet published that the logic of digital visibility has changed. Future organic traffic won't come from ranked keywords, it will come from being the entity that language models use to ground their answers, the same reasoning behind our [guide to appearing in ChatGPT (AEO/GEO)](/en/blog/como-aparecer-no-chatgpt-guia-aeo-geo/). AI will only use your data if your brand is unimpeachable. And building that unimpeachability, through consistency, authority, and constant updates, is exactly the work of GEO. The official report is available at: [\[A Pragmatic Approach to AI Governance in America, Google, June 2026\]](https://blog.google/company-news/outreach-and-initiatives/public-policy/white-paper-ai-regulation/) * * * Grounding explains why Google cites a source. The guide [how to appear in ChatGPT, Gemini, and Perplexity](/en/blog/como-aparecer-no-chatgpt-guia-aeo-geo/) covers the same logic applied to conversational engines, with the technical steps (schema, JSON-LD, crawlers, llms.txt) to get there.