Press Releases Aren’t Just for Journalists Anymore: 4 Ways to Make Releases More AI-Friendly

Let’s be honest: reporters and editors don’t always have time to clearly and carefully read a press release from top to bottom. They skim, scan and pull the essentials. Increasingly, that work isn’t being done by humans at all — it’s being handled by AI.

Large language models (LLMs), AI-powered search tools and automated news scrapers now summarize announcements in seconds. That means press releases aren’t just speaking to journalists anymore. They’re speaking to machines that decide what gets extracted, paraphrased and surfaced to audiences. And those systems tend to reward what’s early, clear and structured.

So, communicators should be asking a new question: If an AI tool had to explain your news in two sentences, would it get it right?

Small summary, big impact

One emerging way organizations are trying to improve their odds is by adding a short, clearly labeled summary immediately after the headline — often called an AI Summary, Key Points or In Brief section. These summaries are designed to present the essential facts upfront: who is announcing what, when it’s happening, where it applies and why it matters.

AI systems generally assume the most important information appears first. When they encounter a clearly labeled summary near the top of a release, they often treat it as the authoritative explanation of the news. In some cases, that summary becomes the text AI tools extract, quote or paraphrase when answering questions or generating overviews. Without that guidance, AI may pull context from deeper in the release or assemble its own interpretation, sometimes missing nuance or emphasizing the wrong details.

Companies, including Aldi, Paramount and Eli Lilly, have begun using AI Summaries or Key Points sections at the top of press releases and corporate announcements. What’s notable is that this adoption is happening ahead of formal measurement — organizations are adjusting based on how information is increasingly consumed, not because the data is already settled.

Best practices

1. Write summaries as original content, not copied lines — The summary should not simply repeat sentences from the release. Reframing improves clarity and helps AI systems accurately interpret the announcement.
2. Label the section clearly — Use headings like AI Summary, Key Points or In Brief so both humans and bots understand the intent of the content.
3. Lead with structure and key facts — Summaries should spotlight the company name, product or announcement, location, timing, and why it matters. AI systems prioritize content at the top of a document.
4. Weigh bullets versus paragraphs — Experts continue to debate this. Bullet-style summaries are generally better for AI reuse and extraction because they present discrete, self-contained facts that systems can easily parse and cite. Paragraph-style summaries are better suited for human-facing narratives where nuance, tone and interpretation matter.

Regardless of format, the goal isn’t marketing language or persuasion. Effective summaries tend to be short, factual and neutral, answering basic questions rather than telling a story. They act as a snapshot — not a substitute for the release itself.

Important considerations

There is no hard data yet — No publicly available, peer-reviewed research definitively proves that AI summaries increase LLM exposure or SEO performance. Many large companies, like Aldi and Paramount, are using summaries or key points, but adoption is happening ahead of formal measurement.

Wire services can make summaries more expensive — Because summaries typically sit at the top of a release, you may need to cut length elsewhere to stay within pricing thresholds.

Summaries should not replace strategy — AI summaries won’t compensate for unclear messaging, weak news value or releases that are too long. They amplify clarity. They don’t create it.

Some communicators argue the only responsible way to evaluate impact is through controlled experimentation — running releases with and without summaries over time and comparing outcomes. Until clearer data exists, AI summaries are best viewed as an emerging practice, not a guaranteed driver of visibility or performance.

At its core, this isn’t about chasing a trend. It’s about understanding how information is discovered and interpreted today — and making sure your message survives that process intact.

If you’re ready to start building AI-ready press releases into your communications approach, connect with me to get started. For an in-depth analysis of how Generative Engine Optimization is transforming visibility, check out this post, 7 GEO Stats Communicators Can’t Ignore.