Milena Traikovich is a prominent figure in the field of demand generation, recognized for her ability to transform complex analytics into high-performing lead-generation initiatives. As the digital landscape undergoes a seismic shift toward AI-integrated discovery, Milena has been instrumental in helping businesses navigate the transition from traditional search to Generative Engine Optimization. In this interview, she shares her expertise on how the fusion of PR and data-driven visibility is redefining the way brands maintain relevance. We explore the emerging metrics used to track presence within Large Language Models and the strategic necessity of prioritizing earned media to secure a competitive edge from 2026 to 2028.
Our conversation delves into the fading boundaries between public relations and search engine optimization, highlighting how Large Language Models favor authentic editorial content over paid placements. Milena discusses the integration of AI Visibility scores into brand strategy and offers a roadmap for restructuring content to satisfy the technical requirements of generative engines while maintaining credibility with human audiences. She also explains why the role of the marketer is shifting toward a more nuanced understanding of media influence.
AI search engines frequently prioritize earned media over paid advertisements when generating responses. How is this shifting the landscape for traditional marketing and PR teams?
We are witnessing a monumental pivot where the art of storytelling is becoming the backbone of search visibility. Recent research reveals that a staggering 82% of the links cited by AI engines are sourced from earned media—the independent voices of press and influencers—rather than a brand’s own paid promotions. Furthermore, 94% of citations come from non-paid media, which sends a clear signal that the era of simply buying your way to the top of search results is effectively ending. This shift is forcing marketing and PR teams to integrate more closely than ever before, as PR budgets are projected to double to accommodate this new demand for AI-friendly coverage. Brands are beginning to pull significant resources away from traditional search engine marketing to fund these PR initiatives, recognizing that a mention in a trusted publication is now a primary driver of search discoverability.
With the introduction of metrics like AI Visibility (AIV) and Media Impact Value (MIV), how should brands realistically measure their success in this new environment?
Measurement has evolved from looking at simple click-through rates to analyzing deep representation within Large Language Models like Google Gemini and ChatGPT. Through tools like the new AIV metric, brands can now quantify their impact across both traditional social platforms and within the responses generated by AI. This dual-scoring system allows a brand to see exactly how much of its total value is coming from editorial sources versus AI-powered search results. By using specialized dashboards, marketers can identify which specific editorial sources are being referenced by AI when their brand is mentioned, providing a clear roadmap for future outreach. It gives a brand the ability to see the actual information LLMs are giving consumers, allowing them to track the narrative being built around them in real-time.
What practical steps should a marketing team take to ensure their brand is accurately and frequently cited by generative AI engines?
The most effective approach is to treat your content as a set of structured data points that an AI can easily digest and reference. This starts with ensuring that your owned content, such as press releases and corporate announcements, is exceptionally clear, factual, and easy for AI systems to parse for key information. You must also become proactive in prompt testing; by regularly entering queries related to your brand into various LLMs, you can see which sources the AI prioritizes and what kind of information it is relaying to the public. It is also vital to use earned and owned media in tandem, leveraging earned media to gain that crucial third-party credibility while using your own channels to clarify facts and technical details. This holistic strategy ensures that you are not just visible, but that the information being shared is accurate and authoritative.
Beyond just generating coverage, how can marketers identify and leverage the specific sources that influence their brand’s visibility in AI search?
Marketers need to move beyond a broad PR strategy and start looking at their media lists through the lens of AI influence. By monitoring which publications consistently appear in AI-generated answers, you can identify the specific journalists and media houses that carry the most weight with current algorithms. These sources often represent highly trusted domains that AI models prioritize because they require up-to-date, verified information to answer queries about recent events. Once you identify these high-influence nodes, you can focus your outreach efforts there, ensuring that every piece of coverage you secure has the maximum possible impact on your AI footprint. This level of strategic focus allows brands to optimize their PR spend and ensure their message is being amplified by the sources that matter most to generative engines.
What is your forecast for the evolution of brand discovery?
I anticipate that from 2026 to 2028, we will see a complete merging of PR and search strategies where the two functions become indistinguishable. As AI becomes further embedded in the consumer’s decision-making process, brands will prioritize “credibility at scale,” focusing less on keyword density and more on securing high-quality mentions that signal authority to both humans and machines. We will likely see a move toward more diverse media budgets, where brands are present across a multitude of surfaces rather than just a single search results page. Ultimately, the winners in this space will be those who recognize that AI requires a strategy that values authenticity and trusted editorial voices above all else. Success will be measured by a brand’s ability to remain current and highly cited within the ever-evolving retrieval systems of these powerful generative models.
