When an old friend of the Hive reached out and asked us to share how AI was impacting earned media and press release approaches, the whole team started geeking out.
It turned into a classic Beekeeper Brainswarm where everyone shared insights we’d gathered across clients, across industries, across the weird edge cases you only find when you’re doing this work day in and day out. So we figured: why keep it to ourselves?
Here are the five big things we walked through.
1: The SEO basics still matter, but the target has moved.
Core search engine optimization (SEO) fundamentals like credible backlinks, site performance, and structured content are still the foundation. What AI optimization (also known as AEO or GEO) adds is a layer on top of that foundation, not a replacement for it.
Google itself has said as much: its AI-generated features are built on the same core ranking and quality systems that have always governed search results. So if you’ve been doing SEO well, you’re not starting from zero.
What has changed is what you’re optimizing for. The old goal was ranking #1 in search results, but the new goal is becoming the source an AI system cites when someone asks a question in your space. This goal shift changes how you write, structure, and distribute content.
2: It’s no longer about the #1 result. It’s about the quoted answer.
AI systems are looking for content that is clear, direct, credible, and easy to extract. AI can’t easily parse through long, complex reports that rely on critical thinking for understanding key takeaways.
That means the “quick answer formula” matters: for any piece of content, ask yourself what question you’re trying to answer, and then answer it specifically, at the top, in plain language.
Structurally, this looks like question-based headers, short paragraphs, chunked information, and the most important content in the first 200-300 words. Readability tools like HemingwayApp are actually useful here! If your content reads like a law review article, AI is probably pulling from somewhere else.
3: Consistency is key, and content is now a long game.
AI doesn’t operate on a news cycle, so a piece of content from 18 months ago can still be the answer it surfaces today. That means every piece of content you publish can be a long-term asset that can build continuous returns.
This should impact your content strategy. AI will be more likely to pull from your content if it sees that you have topic/organizational credibility, information that is easy to cite, and has a clear point of view. If you publish content that clearly establishes a fact, a position, or a definition, that increases the long-term value of the content in the ‘eyes’ of an AI system. Named bylines signal credibility and build a track record that AI systems recognize over time.
The practical implication: think about content in clusters, not one-offs. A single topic should generate multiple pieces (a press release, a blog post, a thought leadership piece, a social amplification strategy) all saying consistent things and linking to each other.
4: Media coverage is now a permanent citation, not a one-day win.
This one hit the team hard when we started thinking through the implications. Every credible outlet that covers you becomes a source AI draws from indefinitely. So media strategy and content strategy have to be much more integrated than they used to be.
What that means practically: outlet authority matters more than clip counts. One strong placement in a credible publication can carry more weight in AI systems than a dozen lower-authority hits. This also means the goal has shifted: you’re not just reaching today’s reader, you’re shaping tomorrow’s AI answer.
5: AI is a jumping-off point, not an end point.
There is a lot of AI generated content out there, but the value of recognizable human expertise (named authors, distinctive perspectives, human voice) is actually going up, not down. The teams that figure out how to use AI to amplify their expertise, rather than replace it, are the ones who’ll be in the best position.
It’s important to remember that generative AI is drawing conclusions based on the available information that is easiest for it to understand and validate by other sources. Within the context of AEO/GEO, AI is intentionally trying to simplify information to form a clear answer for the asker; it is functioning more like a summarizer than a critical thinker. This is why it’s crucial for communications professionals to be focused on defining a clear strategy for their work. Effective communications built for humans and AI will need to start from a place of clear expertise, data-backed positioning, and a strong message.
Inspired by our earned media brainstorming session, our team built out an example of an AI-powered media brief that pulls overnight news, competitor activity, and coverage signals into a single daily summary. The benefits are two-fold, it helps us stay up to date on the issues relevant to our clients, and it helps us see if our AEO/GEO earned media strategies are working.
There’s more where this came from. We went deep on press release structure, link strategy, and how to audit existing content against these principles. If any of this sparked questions, you know where to find us.