94% of B2B buyers now use AI during their purchasing process, but McKinsey found that your website accounts for just 5 to 10% of what AI references. This guide covers the practical principles for writing blog posts and press releases that work for both human readers and AI agents, based on peer-reviewed research from Princeton University, Forrester and others.

By Helenor Rogers, CEO of Known Entity

Blog posts and press releases now need to serve two audiences: human readers and AI agents. To be cited by AI platforms like ChatGPT, Perplexity, Claude, Gemini and Copilot, content must lead with clear answers, include specific statistics and source citations, use logical heading structures, and be written in self-contained paragraphs that an AI agent can extract without surrounding context. Consistency of messaging across all channels and third-party sources is equally critical, because AI agents build their understanding of a business from dozens of independent references, not just your website.

If AI agents can't extract a clear, confident answer about your business from the sources they trust, you won't appear in the buying conversation at all.

This matters now because of how rapidly AI is reshaping buyer behaviour. Forrester's State of Business Buying 2026 found that 94% of business buyers use AI during their purchasing process, and that generative AI searches are now the starting point for B2B purchase research. You can read about this in more depth in our White Paper: The Invisible Shortlist. McKinsey's AI Discovery Survey (October 2025) found that a brand's own website accounts for only 5 to 10% of what AI search references, with 90 to 95% coming from third-party sources including editorial coverage, review sites, user-generated content and affiliates. For most businesses, the content they control directly has almost no influence on what AI tells their potential customers about them.

So now to some clear definitions. Generative Engine Optimisation (GEO) is the practice of structuring content and digital presence so that AI platforms cite your business in their generated answers. Answer Engine Optimisation (AEO) describes the same discipline, they are interchangeable. Both sit apart from traditional SEO, which optimises for search engine rankings rather than AI citation. GEO and AEO require a different approach to how organisations write, structure and distribute their content.

AI Authority is the practice of ensuring a business is accurately and consistently represented across the sources that AI agents use to generate answers. At Known Entity, the specialist AI Authority consultancy I co-founded, we help B2B and branded organisations build this capability using a structured methodology called the AI Authority Ladder™. The AI Authority Ladder™ is a four-stage process:

  1. Diagnostic — how AI currently sees your business
  2. Knowledge Graph build — which we call the EntityCore X™, creating the content AI agents can read
  3. Citation strategy — building third-party references that AI trusts
  4. Ongoing measurement — tracking citation performance across platforms and updating the EntityCore X™

Here's what the research says about getting your content right.

How AI agents retrieve and evaluate content for citation

AI agents don't browse websites the way people do. They use a process called Retrieval-Augmented Generation (RAG), which retrieves passages from a pre-indexed database, scores them for relevance and confidence, then synthesises those passages into a response. This means AI agents are looking for specific things in your content: clear claims, verifiable facts, attributed sources and structured answers. Content that delivers these signals gets cited. Content that doesn't is invisible, regardless of how well it ranks in traditional search.

Research from Princeton University and Georgia Tech, published at ACM SIGKDD 2024, tested nine content optimisation strategies across thousands of content samples and found that including specific statistics improved AI visibility by 41%, adding citations to authoritative sources improved visibility by up to 40%, and for lower-ranked websites, citing credible external sources improved visibility by 115%. Keyword stuffing performed 10% worse than the baseline. The evidence is clear: AI agents reward substance and verifiability, not volume or promotional language.

Six principles for writing blog posts that AI agents will cite

The following principles are drawn from peer-reviewed research and large-scale industry analysis. They apply to blog posts, press releases, by-lined articles and any content you want AI agents to find, extract and reference.

Why AI-optimised content reads differently to traditional marketing copy

You may have noticed that this article reads differently to a typical blog post or opinion piece. The headings are descriptive rather than clever. The opening paragraph states its conclusion upfront rather than building to a reveal. Statistics are attributed inline rather than waved at vaguely. That's deliberate. This piece has been written to follow the same principles it describes, because if we're going to advise others on writing for AI agents, the least we can do is practise it ourselves. The result is a style that feels more like a reference guide than a newspaper column, and that shift in tone is something all of us in marketing and communications will need to get comfortable with. The content that AI agents choose to cite is structured, specific and direct. The content they skip is often beautifully written but too loosely structured for a machine to extract with confidence.

Why brand consistency across channels determines AI visibility

AI visibility is determined more by the consistency of third-party brand mentions than by anything on your website. Most businesses focus their content efforts on their own domain, but because AI agents draw 90 to 95% of their references from third-party sources (McKinsey, October 2025), the way your brand is described across the wider web is the primary factor in whether AI agents cite you or a competitor.

Ahrefs research (2025) found that brand web mentions correlate three times more strongly with AI visibility than backlinks, with a correlation of 0.664 for mentions versus 0.218 for links. This means consistent, accurate descriptions of your business across independent sources, including trade press, directories, LinkedIn, review sites and partner websites, are significantly more valuable for AI discoverability than traditional link-building. For businesses that have invested heavily in SEO and backlink strategies, this represents a fundamental shift in where visibility is actually built.

AI agents build their understanding of a business by cross-referencing multiple independent sources. If your blog describes you as a "specialist advisory firm," your trade press coverage calls you a "consultancy," your LinkedIn headline says something different again, and your industry directory listing is two years out of date, the AI agent receives conflicting signals and may default to a competitor whose story is clearer and more consistent.

In AI search, a fragmented brand story is worse than no story at all, because it actively undermines the confidence an AI agent needs to cite you.

An entity definition is the understanding that an AI agent holds about what a business is, what it does, and who it serves. AI agents construct this definition by cross-referencing every available source, and inconsistencies between those sources reduce the agent's confidence in citing the business. At Known Entity, the first rung of our AI Authority Ladder is a diagnostic that maps exactly how AI agents currently understand a business: what they say about it, what they get wrong, where they cite competitors instead, and where the gaps sit. For most organisations, fixing the entity definition is where the work needs to start.

How to write press releases that AI agents will index and cite

Press releases are one of the most effective tools for building AI citation, because they generate the third-party coverage that AI agents trust most. They now need to serve two audiences simultaneously: the journalist who might cover the story and the AI agent that will index both the release and any resulting coverage. A press release that reads like a marketing brochure won't get cited by AI. A press release that is structured for extraction will.

If this format sounds familiar to anyone who has worked closely with journalists, it should. A clear description of who you are, specific facts, attributed quotes, consistent language and a logical structure: this is actually what good news desks have always wanted from a press release. The format that AI agents reward is, in many ways, a return to strong press release discipline rather than a departure from it. The releases that struggle with both audiences are the same ones: vague, strapline-led, full of phrases like "we're thrilled to announce" and light on verifiable substance. Writing for AI citation and writing for journalist pick-up turn out to be far more aligned than most communications teams expect.

Why earned media is the primary driver of AI citations

Earned media is the single most important factor in AI citation. Muck Rack's analysis of over one million AI citations (2025) found that 82% came from earned media sources and 95% from non-paid sources. Press coverage, expert commentary in trade publications, by-lined articles and contributions to industry discussions are the sources AI agents trust and cite most frequently. Paid content and owned marketing material account for a small fraction of what AI agents reference.

Owned content, including your blog, website and knowledge base, plays an important supporting role. But it plays that role most effectively when it's part of a wider ecosystem of consistent, credible content that extends well beyond your own domain. The organisations building real AI Authority are the ones that treat every piece of content, owned and earned, as part of a single coherent signal to AI about who they are and what they know.

AI Authority is not about gaming an algorithm. It is the practice of ensuring that the right information about your business is available, structured and consistent across every source an AI agent might consult, so that when a buyer asks an AI "who are the leading specialists in X," your business is in the answer. Organisations that do not actively manage their AI Authority risk being absent from the consideration set entirely, because AI agents will recommend the competitors whose information is clearer, more consistent and easier to cite.

How to start building AI Authority for your business

Building AI Authority requires a structured approach that spans content strategy, earned media, entity definition, structured data and ongoing measurement. It sits at the intersection of skills that most marketing teams don't yet have in-house, which is why it's emerging as a specialist discipline.

Known Entity is a UK-based AI Authority consultancy that works with B2B and branded organisations to ensure they are accurately represented and consistently cited by AI platforms including ChatGPT, Perplexity, Claude, Gemini and Copilot. Founded by a team with backgrounds in marketing strategy, technology and content, we use our proprietary AI Authority Ladder™ methodology to take businesses from invisible to appropriately and strategically cited, step by step.

"Most businesses we speak to assume the goal is simply to appear in AI answers. But appearing for the wrong things, or in the wrong context, can be just as damaging as not appearing at all. The real work is ensuring AI agents understand what your business genuinely stands for, and cite you for the things that matter to your commercial strategy. That's what we mean by being properly known."

— Helenor Rogers, CEO of Known Entity

If you'd like to understand where your business currently stands in AI search, and what it would take to close the gap, get in touch at hello@knownentity.ai or visit knownentity.ai.

Last updated: 7 April 2026

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