Generative AI platforms, large language models (LLMs), Silicon Sages, Byte Bards. Call them what you will. Quite the hot topic. These tools are rapidly changing how we use the internet and how brands try to get our attention online.
In this article, we explore why good content and great digital PR still matter (maybe now more than ever)—and how to connect with consumers in the AI era by mastering LLM optimization (LLMO) also known as Generative Engine Optimization (GEO). This topic has become increasingly important as AI continues to transform the digital landscape.
(Spoiler alert: The fundamentals of high-quality, relevant content still very much apply. It turns out everybody’s still got to E-E-A-T. 😋)
SEO Before the Dawn of LLMs and Generative Engine Optimization (GEO)
Let’s first take a look at how the internet worked before language models began eating into the traditional search engine market share and changing how we use the web.
You’ll remember that, until fairly recently, you’d simply open a browser and go to Google Search to find the direct answer to your burning question. You’d type a query into the search bar, prompting the search engine to crawl through billions of web pages and return links that best match your search terms and give you a concise answer.
Google’s algorithm prioritized sites it deemed authoritative and relevant, considering factors like backlinks, topical expertise, domain authority and trustworthiness when determining which links to display in its Search Results Pages (SERPs).
High-quality links from credible sites boosted a page’s authority while consistently covering a subject in depth established a site as a relevant source of information.
Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, and Trustworthiness) played a massive role in assessing content creators’ expertise and whether all the other information on the site could be trusted.
Relevance depended on how well a site answered search queries and met user intent. Websites that provided accurate, trustworthy, and reliable content were more likely to rank higher in search results.
An entire search engine optimization (SEO) industry emerged around this system. Companies looking to put their products in front of internet users and outrank competitors began crafting content designed to convince Google they were the most authoritative, knowledgeable, and trustworthy option.
If you typed “What’s the best mattress?” into Google, for example, the results would be determined not necessarily by which company had the best product but often by which business had invested most heavily in SEO. This also didn’t mean the two were mutually exclusive.
When ChatGPT was launched in November 2022, consumers quickly realized they could bypass traditional search engines entirely and receive a quick answer in conversational form from the friendly chatbot in their browser.
A prime example of this efficiency and pertinence in today’s search experience is when looking for a food recipe. Remember, before AI-powered systems, when you had to read the author’s entire life story before getting to the actual measurements and meaty bits? Not so anymore.
When ChatGPT was born, the era of LLM-based search—and a massive paradigm shift—had arrived.
How LLMs Find Your Content
If you’re set on using language model platforms like ChatGPT, Gemini and Claude to amplify your brand’s messaging, it’s essential to understand how large language models find the information they serve after receiving a prompt.
LLMs are trained on vast amounts of data, including information that lives on websites and social platforms, in articles and videos, and user-generated content on sites like Reddit. Unlike traditional search engines, which rank results based on relevant keywords and strong backlinks, AI-powered search generates responses based on context, user interaction, meaning, and source credibility.
Still tossing and turning? 😩 When you search for that mattress using an LLM-based search, the LLM prioritizes information based on a different set of key factors—not all that different from how Google ranks content.
If you love a good acronym, think PRUFA:
- Popularity: The LLM considers what other users found useful, like frequently visited pages or highly shared content.
- Relevance: It looks for content that gives you a direct answer, like mattress buying guides, reviews, or comparison sites.
- User intent: It tries to understand what you’re really looking for based on relevant keywords, whether it’s price comparisons, best-rated options, or mattress types.
- Freshness: It prioritizes up-to-date information, ensuring you see the latest product releases and reviews.
- Authority: It favors well-known, trusted sources, such as major retailers, expert blogs, and review sites with strong reputations.
If you type up a question like “what is the best quality mattress out there?,” in the search bar, an LLM-backed system will likely prioritize trusted product review sites, major retailers, and expert recommendations over random, unverified blogs. While the AI platform compiles information from across the internet rather than simply matching you with links, the fundamentals of E-A-T still apply.
The bottom line? SEO isn’t dead. It’s simply evolved to focus on a different type of search function.
In this approach, the core principles remain important, but succeeding in this new world requires a good understanding of LLM optimization—and updated PR strategies. Keywords still matter, but brands set on winning new customers must incorporate additional tactics, such as co-occurrence optimization and citation optimization, to stay competitive.
Let’s explain.
Co-Occurrence, Citation Optimization, and the Evolution of Backlinking in LLM search
Co-occurrence optimization refers to strategically managing where and how your brand’s product or service appears alongside other relevant content online.
Take the mattress example—except, this time, you’re the manufacturer:
If your product frequently appears in articles about sleep or its health benefits, it establishes a strong contextual link known as co-occurrence. If a health influencer praises your mattress for its comfort and superior quality, and this gets picked up by a news outlet that shares the review to the far reaches of the internet, you’ve hit co-occurrence gold.
Citation optimization is the next evolution of backlinking. Instead of just earning links from other websites to yours (traditional backlinking), this practice focuses on getting your brand’s product or service cited by credible, widely recognized sources—e.g., media publications, industry publications, review sites, directories, or other trusted brands—without necessarily linking back to your site.
To position your brand effectively in a landscape where co-occurrence and citation optimization matter, focus on creating structured, authoritative, and widely recognized content that AI can easily process, validate, and reference.
Well-written press releases and other types of content shared enthusiastically via earned and owned media channels can prime your brand for AI-driven search results and recommendation systems.
How To Help Your Brand Rank in AI Search Results
Your toolkit as a PR professional remains the same, but how you use formats like press releases to grow your digital presence has evolved.
Here are three ways of making your content discoverable by LLMs:
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Strategically structure your press releases
Press releases remain a powerful tool for building brand visibility and awareness, and establishing trust and credibility. In 2025, when consumers are leaning harder on LLMs for information, their content and structure are more critical than ever.
Since AI models rely on clean, well-organized data to generate answers, a structured press release improves discoverability and citation by LLMs, strengthening your Generative Engine Optimization (GEO) efforts. When your press release is used by an LLM, it also improves your chances of getting picked up by newsrooms, who—no surprise—look for the same qualities in content as LLMs.
Best practices:
- Use clear headlines and subheadings to improve readability and indexing.
- Ensure factual accuracy and include verifiable data points to build trust with AI models. The data should ideally be sourced from official reports, credible news sources, scientific studies, or authoritative industry data.
- Publish press releases in multiple formats, including text, video, and infographics, to enhance reach across different AI-driven search platforms.
2. Push for reviews, mentions, and citations
AI models prioritize information from authoritative sources.
So, if a trusted news outlet, analyst, or industry expert mentions your brand, it significantly increases the likelihood of being referenced by AI in relevant queries. The mention acts as third-party validation, boosting your brand’s credibility in AI-generated results. But getting these mentions can be hard work.
Best practices:
- Build relationships with journalists and influencers in your industry to secure mentions in authoritative publications.
- Engage in thought leadership by contributing expert commentary to news articles, blogs, and industry reports and creating your own thought leadership content.
- Monitor and respond to AI-generated results about your brand, correcting misinformation when necessary.
- Leverage high-quality backlinks from authoritative sources to reinforce credibility in AI ranking algorithms.
3. Regularly refine and update your owned media assets
Your website, blog, online newsroom, social pages, and product updates are the foundation for Generative Engine optimization.
AI models rely on structured, authoritative, and well-maintained information sources to generate responses, making your owned media a critical asset.
Best practices:
- Maintain an AI-friendly website with clear navigation, structured content, and updated metadata.
- Interlinking between content helps generative AI search engine bots understand the relationships between different pages or pieces of content on a website. By linking related content, you create a clear structure that helps bots crawl the site more efficiently and understand how individual pages are connected.
- Regularly publish blog posts, product updates, and industry insights that establish topical authority.
- Include structured data (technical SEO) to help AI categorize and understand the content. This data helps generative AI search engines understand the article’s title, author, publication date, keywords, and description, improving its chances of being accurately indexed and appearing in prompt answers. LLMs don’t directly use structured data when generating responses, but the content used to train them can come from structured datasets that include metadata.
- Centralize all press releases, articles, and brand updates in an online newsroom to create a single authoritative reference point for AI systems.
The Role of Good PR in Search
PR professionals with good insights into SEO best practices and experience in the foundations of creating valuable content—for people and bots—continue to play a crucial role in determining search visibility for the brands they serve. Content humans find valuable translates into content that gets picked up by Google and LLMs.
One of the underlying dangers of AI is a race to the bottom, where “empty” content is created by prompters with no experience. In 2025, quality matters more than ever. A press release, a Q&A, a case study, or an interesting report on the topic of sleep is useful to the person looking for a mattress. And trust us: In the age of AI, this isn’t the time to sleep on it.
If you need help structuring your brand news—and making your content come alive in a sleek online newsroom—schedule a PR.co demo.
