If you work in communications or run a business, you have probably already asked yourself whether AI is just another technological fad or a real tool that can significantly improve your PR results. Globally, that debate has long been settled. Today, 76% of PR professionals use generative AI daily — most commonly for writing, editing and research.

In Bulgaria, the picture is more varied. Some companies are actively experimenting, others are watching from the sidelines, while some are still wondering whether to take the first step at all. Meanwhile, the reality of the media landscape is becoming increasingly unforgiving. Journalists receive dozens of press releases every week, and the time they spend on each news item in their inbox rarely exceeds ten seconds. In short — the competition for attention has never been fiercer.

That is why the big question today is not whether AI will replace PR professionals, but how it can improve the quality of PR services. Because, whether we like it or not, AI is already the tool tipping the scales between a news story that gets ignored and one that gets published.

PAINFULLY FAMILIAR PROBLEMS

We sent a press release to 30 media outlets — only two published it. We work with an agency, but the results are unpredictable. Our competitors are constantly in the media; we are not.

And the most painful admission of all: Our press releases sound like everyone else’s.

This is not a lack of effort. It is a collision with the reality of today’s media environment.

The market is saturated with corporate news. Journalists increasingly have little time to “finish” or reshape texts — they are looking for publication-ready material, while attention is a limited resource everyone is fighting for.

Today, the winner is not the one who sends more. It is the one who sends more precisely, more intelligently and more relevantly.

HOW AI SOLVES SPECIFIC PR PROBLEMS

“Nobody reads our press releases”

In most cases, the problem is not the news itself, but the fact that we tell the same story to everyone.

With the help of AI, it is now entirely realistic to analyse dozens of recent pieces by a specific journalist — what topics they cover, what angles they prefer, what words they use and how they structure their stories. For example:

– for a journalist covering innovation, the emphasis falls on the technology and the product;

– for a business reporter — on the impact on costs, turnover or the market;

– for a lifestyle publication — on the benefits for people.

The result is tangible. In practice, personalised news pitches can often increase publication success rates from around 5% to 25–30%. A change that can transform the overall impact of a campaign.

“Our headline doesn’t grab attention”

The headline is the first — and often the only — chance you get.

AI makes it possible to generate and test dozens of variations in seconds, comparing readability, emotional response and SEO potential. The contrast between Company X Introduces a New Service and Company X Cuts Costs by 40% with New Platform is the difference between “read” and “skipped”.

The value here is not in having the machine write for you, but in having it show you which formulas work — and why.

“We don’t have time for follow-up content”

A truly good press release rarely lives for just one day.

With the help of AI, the main text can quickly become an entire content ecosystem: a LinkedIn post for the company account, a more conversational version for Facebook, a series of posts for X, several versions of emails to journalists, an Instagram caption, a blog article for the website.

What used to take half a working day can now be done in around half an hour. It is no coincidence that data shows AI can reduce the time spent on PR and marketing tasks by up to 70%.

“We don’t know whether our text is strong enough”

One of AI’s most practical roles is that of a “second pair of eyes” before a press release goes out.

Systems can now suggest whether a topic has genuine news value, whether the headline works, whether the tone is appropriate and even whether the timing is right.

A practical example: sending a release on Friday afternoon. The analysis shows that between 3:00 and 5:00 p.m., readership drops by around 60%, and recommends Monday morning instead. A small change that can often have a major impact on the outcome.

“Our press release can’t be found on Google”

Today, visibility does not end with publication.

AI makes it possible to optimise content in real time based on actual search queries, Google’s content presentation structure and the descriptions that perform best. In fact, companies that systematically use AI for SEO report up to 45% growth in organic traffic and significantly better long-term visibility.

WHAT AI CANNOT DO

However impressive its capabilities may be, there are areas where AI remains an assistant — not a replacement.

The first and most important is strategy. AI can analyse data and suggest options, but it cannot confidently say, “This is not news” or “Now is not the right time.” It does not sense the political, social and cultural context. It does not know when a topic is sensitive, when it is risky and when it is simply inappropriate.

The same applies to media relations. AI does not personally know journalists. It does not know who prefers a phone call, who wants a short email and who would rather hear the story first. It does not know the unwritten rules and dynamics within newsrooms — nuances that often determine the fate of a piece of content.

In crisis situations, this becomes even clearer. AI can be technically accurate but tonally wrong. And in a crisis, tone is everything. A single word without empathy or with the wrong emphasis can deepen the problem instead of solving it.

And finally — creativity. AI works with patterns that already exist. But the intuition to recognise which story has the potential to become big, what will capture the public imagination and what will go unnoticed remains deeply human.

THE HYBRID MODEL: BEST PRACTICE

The most effective approach today is not “AI instead of humans”, but AI together with humans. In practice, this usually means:

  • strategy remains human;
  • research is heavily supported by AI, but with mandatory human verification;
  • writing is shared — ideas and structure come from the human, while AI provides rapid processing and variations;
  • personalisation is automated, but the final nuance remains human;
  • analysis is almost entirely automated.

This model does not make PR more impersonal. On the contrary — it makes it more predictable, more measurable and significantly more effective.

When AI is used correctly, the impact goes beyond convenience. Companies report faster content creation, more media coverage, greater visibility and higher engagement. Most importantly, however, the link between PR activity and real business results becomes much clearer and more measurable.

WHAT COMES NEXT

In 2026, success in PR is not determined by budget, but by how intelligently a PR team works. AI is not a future waiting to happen. It is a reality that is already rewriting the rules of the game. Companies that use it strategically are no longer asking whether AI has a place in communications. They are learning how to use it even more effectively.

Passive observation or competitive advantage? That is the question.