Why Digital PR Needs a Rethink in the Age of LLMs
What gets linked may no longer be what gets remembered. In an AI-powered search landscape, it’s context that carries weight.
I started out in digital PR over four years ago, building media lists, pitching stories, and chasing backlinks. These days, I work in SEO innovation and AI development, building tools that sit at the intersection of search, content, and strategy.
Search has changed. And with it, the role of digital PR is shifting too. Here’s how I see the landscape evolving, and what great PR content looks like in the age of AI.
New rules, new signals
Search is evolving fast. And for brands that understand what’s happening, there’s a real opportunity to get ahead.
We’re no longer just optimising for traditional search engines. We’re optimising for systems that read, understand, and learn.
Large Language Models (LLMs) like Gemini, GPT-4, and Claude have changed how people interact with information. These models don’t just retrieve content — they interpret it, embed it, and retain it for future use.
That means the articles, quotes, and stories we place as digital PR professionals are no longer just coverage. They’re training data. They’re signals that help AI form an understanding of who a brand is and what it stands for.
Traditional search ranks pages based on keywords and backlinks. AI-powered search understands content in context, ranking based on meaning, authority and intent.
From keywords to concepts
Search used to be about matching specific words. Now, it’s about matching meaning.
Modern AI search systems use vector embeddings to understand context, relevance, and intent, instead of just matching keywords.
In this new paradigm, LLMs map content relationships in high-dimensional spaces, similar to knowledge graphs. These relationships are learned during training and evolve as models are exposed to more data or fine-tuned. In retrieval-based systems, like RAG or search engines, real-time content is pulled in and processed to update the model’s understanding and generate responses.
Brand mentions that align with a model’s understanding of the brand will reinforce positive associations. Inconsistent mentions may create confusion. PR content helps shape brand perception by building meaningful relationships that the AI internalises and updates over time.
If your brand earns:
- A positive mention in a trusted source
- Clear alignment with your expertise
- Informational depth that gets cited or summarised
You’re not just building visibility. You’re building brand meaning in a language AI understands, ensuring your brand is accurately represented in real-time search results.
Content is now infrastructure for AI
Some of the tools people use every day, like Perplexity and ChatGPT’s browsing mode, work by retrieving live content and feeding it into a language model to generate an answer. While only Perplexity follows a classic Retrieval-Augmented Generation (RAG) structure, the idea is broadly the same.
We’re now also seeing this approach roll out at scale. Google has begun integrating Gemini into Search, with AI-generated overviews appearing for a growing number of queries. These overviews are based on content retrieved from the web in real time and summarised by the model.
Here’s a simplified view of how this process works:
- Relevant documents are retrieved in real time
- Text is broken down into semantically meaningful sections
- These sections are fed into an LLM to answer a query
So when someone asks a question, your media coverage or blog content could help shape the answer — if it’s relevant, clear, and well-structured.
We’re not just writing for people or for search engines anymore. We’re writing for both, and for the systems that sit in between.
What AI-optimised PR content looks like
If you work in digital PR, your job isn’t just to generate coverage. It’s to get your brand seen, understood, and included in the broader narrative.
In this new landscape, effective content should:
- Show expertise through original data, commentary, or research
- Align with a consistent and strategic theme
- Be structured with clarity — headlines, summaries, metadata all matter
- Appear across reputable sources to build strength and relevance
This isn’t just good PR. It’s high-quality training data for AI.
Five ways to optimise your next campaign:
- Design for retrieval
Assume your content will be processed by AI. Use structure, headings, and clarity to make it easy to interpret. - Prioritise informational value
Substance matters more than stunts. Rich, original content will carry more weight and be more reusable by LLMs. - Own your topic
Build consistent association with key themes. Repetition across campaigns builds topical authority over time. - Provide ready-to-use resources for journalists
Journalists are busy and work under tight deadlines. Make their lives easier by providing data, expert commentary, and content that is ready to be used. Offer well-researched, quote-ready text or insights that they can easily copy and paste into their stories. This not only controls the narrative but also ensures your brand’s messaging is aligned and consistent. - Test with AI
Use a model to summarise or critique your work. If it can’t accurately capture your message, the content needs refining.
Digital PR’s strategic opportunity
Digital PR is no longer just a bolt-on to SEO. It’s becoming the semantic layer of search strategy.
We’re shaping the narratives that LLMs internalise and reproduce. We’re influencing how brands are understood across chat, search, and discovery. We’re creating content that AI systems learn from.
Backlinks still matter, but meaning matters more.
In this new era, PR teams have the chance to lead — to bring creativity, insight, and relevance into a search world that’s no longer about keywords, but about meaning.
