Public relations is dead. Long live public relations.

An International Perspective: From Optimization to Influence

In traditional Internet logic, search engine optimization dominated: keywords, rankings, clicks. With AI-powered response systems, the focus is shifting toward influencing machine-generated content. It is important to make this distinction: Depending on the context, such systems draw on indexed web content, retrieval mechanisms, partnerships, and other data sources. It is less about „use“ in the sense of a uniform technical process and more about the interplay of discoverability, citability, and relevance signals.

Therefore, what matters is no longer just whether a brand is mentioned, but in what context, with what tone, and with what consistency across various sources. Recurring patterns in media reports, studies, expert articles, and institutional content shape how topics are framed in AI responses.

As a result, earned media is gaining importance, though this trend must be viewed in a nuanced way: Analyses show that a large portion of the content referenced in AI responses comes from so-called earned sources. An analysis by Muck Rack (based on millions of links in AI responses) finds, for example, that around 27% of the content comes from journalistic sources, along with a much broader definition of earned media—accounting for over 80%—which also includes research, government sources, and encyclopedias. At the same time, other analyses show that corporate websites, product pages, documentation, and community platforms also play a significant role. The conclusion is therefore: Those who are present in trustworthy third-party sources increase their chances of appearing prominently in AI responses, even when they engage in extensive self-promotion.

At the same time, AI is automating a growing portion of operational PR work: monitoring, clipping, sentiment analysis, media lists, reporting, and benchmarking are increasingly supported by algorithms. Tools analyze mentions in real time, identify relevant contacts, and help evaluate the response. As a result, value creation is shifting toward strategic tasks such as topic leadership, narrative design, and issue management.

 KI-Discoverability as a New Core Task

The key question is: How can an organization be represented reliably, accurately, and effectively in AI-powered response systems?

There are four key dimensions to consider. First, technical visibility: content should be indexable, structured, and tagged with clear metadata. Open accessibility is often an advantage here, but it is not always mandatory, as licensed content or content integrated through partnerships can also be considered. Second, source authority plays an important role. Systems tend to give greater weight to sources considered consistent, established, and trustworthy, such as media outlets, specialized portals, or institutional websites. Third, semantic clarity is crucial. An organization’s presentation should be consistent across various channels, creating a stable and unambiguous content profile. Fourth, the reputational context influences the perception of a topic. Different tones are factored into the evaluation, and the aggregated overall impression helps determine how a topic is described and categorized.

Media relations thus becomes a means of creating a coherent information and source base. Content functions less as direct „training data“ in the strict sense and more as signals for search, retrieval, and response systems. Press releases, technical articles, and other formats should therefore be prepared in such a way that they are easily accessible for both humans and machine processing: clearly structured, fact-based, and consistently linked.

The Swiss Context: Media Concentration and the Relevance of AI

Switzerland has a unique situation: a multilingual yet comparatively concentrated media market. According to Medienmonitor Schweiz, key shares of influence are distributed among, among others, SRG SSR (approximately 28%), TX Group (approx. 14%), CH Media (approx. 10%), and other players such as Ringier and international platforms.

The public service broadcaster SRG SSR plays a central role through its subsidiaries SRF, RTS, RSI, and RTR, which together cover a large portion of basic audiovisual services.

In the private sector, key players include, in particular, the TX Group (including 20 Minuten and Tamedia titles such as the Tages-Anzeiger), Ringier (including Blick and Bilanz), CH Media (including Aargauer Zeitung, Luzerner Zeitung, watson, and radio and TV offerings), and the NZZ Media Group are among the key players. In particular, TX Group and Ringier pursue distinct platform and marketplace strategies, while NZZ and CH Media focus more heavily on journalistic content, digital products, and marketing models.

With regard to AI discoverability, a plausible—albeit not directly empirically substantiated—conclusion can be drawn from this: A relatively limited group of established media brands shapes a large portion of publicly visible coverage in Switzerland. Since AI systems draw on such publicly available sources, it can be assumed that these media outlets also indirectly form the basis for many AI-generated responses on Swiss topics. However, this assumption should be understood as an analytical inference rather than a confirmed finding.

At the same time, multilingualism, federal structures, and international media interconnections mean that topics are interpreted differently in German-, French-, and Italian-speaking as well as global information spaces.

The Importance of Trade Media and Special Interest Publications

Trade and special-interest media could take on new strategic significance in the age of AI. While traditional public relations has long focused heavily on reach, thematic authority, subject-matter depth, and semantic consistency are becoming increasingly relevant for AI-powered response systems. Specialized publications provide precisely these signals. Repeated coverage in recognized industry media can help establish stable attributions of expertise and thematic connections that will later become visible in AI-generated responses. Media relations should therefore be evaluated not only in terms of reach, but increasingly in terms of their impact on an organization’s long-term information and source architecture.

An article in a widely read daily newspaper generates public attention. An expert article in a respected industry publication, on the other hand, can have a greater impact on how a company or topic is perceived within the field.

Particularly for B2B companies, technology providers, industrial firms, consulting firms, and healthcare organizations, there is likely to be a high probability that AI systems will use specialized sources as key indicators of expertise and credibility.

New Job Descriptions for Media Relations

The interplay between AI systems and media structures is giving rise to new demands on communications work. At the heart of this is the integrated management of visibility across various levels.

This includes, in particular, systematic earned media management with a focus on credible third-party sources, as well as close integration of PR, SEO, and content strategy to ensure consistent messaging across various channels. Equally important is the development of structured and machine-readable knowledge resources, such as FAQ pages, white papers, or studies. In addition, AI tools can be used for monitoring, analysis, and scenario development to identify trends early on and support strategic decision-making.

«Media relations is dead» thus describes the end of a purely journalistic way of thinking. «Long live media relations» stands for its transformation toward the strategic shaping of visibility in a hybrid information system in which human and machine reception are inextricably linked.

Christian Wick is a federally certified PR consultant, former president of the ZPRG, managing director of the agency WickPR AG, and senior PR advisor at the branding agency The Brand Office, as well as a co-founder of MeinNetz GmbH, a consulting network specializing in data management, data communication, and digital transformation.