Media Monitoring in the Age of AI

Many solutions focus primarily on how often a company, product or competitor appears in the media or in answers generated by ChatGPT, Perplexity and other similar platforms. Good to know, certainly, but not yet a sound basis for decision-making.

From our perspective, what really matters is what lies behind the numbers:

• In what professional or technical context is a company mentioned?
• With which topics and areas of expertise is it associated?
• What are the sources shaping its perception?
• How are competitors positioning themselves?
• And, perhaps most importantly, what drives subsequent communication strategies?

The last point is crucial, as this is where many tools fall short. A dashboard may show that visibility is rising or falling but it does not necessarily explain why this is happening, or what a company should do to improve its positioning.

There is also a particular challenge in the markets in which we work. For R&D, procurement, marketing and management teams, trade media remain central sources of information. Yet much of the relevant content appears in e-papers, print editions orbehind paywalls. As a result, purely automated monitoring solutions only capture part of the picture.

What used to be done manually - finding and collecting clippings - is now handled by analysis of trade media via our akp Media Intelligence Hub. We not only evaluate individual online mentions, but also complete issues of relevant trade publications.

This enables us to identify, for example:

• Which topics are becoming more significant
• The subjects competitors are regularly highlighting
• Companies that already occupy specific topic areas
• Credible opportunities for a company’s own communications

The real value, therefore, does not come from adding more KPIs – it comes from combining data, industry knowledge and communications strategy. Only then does monitoring become genuine media intelligence and a basis for topic planning, media relations, content development and positioning.

The same applies to monitoring AI systems. Technically, many platforms can automatically send a catalogue of questions to ChatGPT, Claude, Perplexity or other such models, and then evaluate responses. But the quality of the analysis depends heavilyon whether those questions reflect the real working environment of relevant target groups. For example, a product developer’s search will differ from that of a procurement manager, marketer or managing director.

That is why we do not see AI visibility as an isolated metric. We see it as part of a broader question: How is a company perceived in its market – by people, the media and, increasingly, AI systems? And how can that perception be influenced in a targeted way?

We have recently published a white paper on this topic - “AI-ready PR for Food B2B” - in which we explore how companies can analyse their visibility in generative search systems, why trade media continue to play a central role and why monitoringshould lead to concrete communications measures rather than simply producing yet another set of statistics. Simply fill in the form below to download your free copy.

Let’s have an open conversation about which form of monitoring and insights will best support your business.

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Get the download link to our white paper "AI-ready PR for Food B2B".