Part 2: Visibility in the Age of AI | The Press Release You Sent Two Years Ago May Still Be Working

Most companies think of a press release as an announcement. Something you send when something happens, and then it's done.

That is not quite how it works.

A press release, once distributed, does not expire. It gets indexed. It gets archived. It gets picked up by industry publications, aggregated by news platforms and stored in the data sets that AI platforms draw from when they construct answers.

The announcement you issued about a product launch in 2023 may still be part of how AI understands what your company does today.

That changes how press releases should be evaluated; not just as a communications tactic, but as a long-term contribution to the public record of your company.

Why persistence matters in AI-driven search

AI platforms are not only reading what was published last week.

They synthesize information across sources and time. When a buyer asks an AI tool to describe a company, evaluate a solution or compare providers, the answer may draw on content that is months or years old such as a case study, a contributed article, a wire release, or an executive interview.

The signals you built over time are cumulative. And so are the gaps.

If your company has been quiet, vague or inconsistent in what you have published, that record follows you into AI-generated answers just as it followed you into search.

A press release is a signal, not just an announcement

The practical value of a press release for AI visibility is not the headline.

It is the information the release contains: who you are, what you do, what problem you solved, which customer trusted you, which market you serve, which expertise you demonstrated.

A well-constructed release gives AI platforms something specific to work with.

A vague press release built around phrases like industry-leading, innovative solution or best-in-class gives AI the same kind of interchangeable language it encounters from every other company in your category.

The result is an interchangeable description of your company.

The specifics matter; a named customer, a measurable outcome, a concrete description of what was built, delivered or solved, and a quote that says something measurable and tangible.

Those details are the signal. Everything else is noise.

What AI is likely looking for in your press history

AI platforms are trying to answer questions buyers are asking.

When a buyer asks which companies specialize in a particular area, AI is looking for evidence: consistent mentions, third-party coverage, documented outcomes, named expertise.

Your press history either builds that evidence or it does not.

A company with several years of substantive releases documenting real customer outcomes, meaningful partnerships, product developments and executive perspectives gives AI more to work with than a company whose public record is thin, inconsistent or filled with announcements that say very little.

The question is not whether your company has been active. The question is whether what you have published adds up to a clear and credible picture.

Volume is not the strategy

Issuing more releases does not solve this.

A high volume of weak releases including routine personnel announcements, reworded product descriptions, generic milestone coverage, adds noise without adding signal.

AI is not counting your press releases.

It is trying to understand what your company knows, what it delivers and why buyers choose it. The releases that contribute to that understanding are worth issuing. The releases that do not probably are not worth the effort, regardless of how they perform on distribution metrics.

The standard for a press release worth publishing is simple: does this document something substantive, and does it communicate something specific about why this company matters?

If the answer is yes, it is likely to have value immediately and over time. If the answer is no, no distribution channel will fix it.

Start by looking at what you have already published

Before thinking about what to issue next, it is worth looking at what is already out there.

Read your last several press releases as if you were a buyer who had never heard of your company. What do they say you do? What evidence do they provide? What impression do they create?

Then ask whether AI would find that body of work useful in constructing an accurate, differentiated description of your company or whether it would be left to fill gaps with generalities.

If the existing record is thin or inconsistent, new releases can begin to address that. If the existing record is substantive, it is already working for you.

The opportunity is to treat press releases not as individual announcements but as deliberate additions to a growing body of evidence about what your company stands for and why it wins.

Next in the series: Are you giving AI more context than you give your customers.