We’re joined today by Milena Traikovich, a demand generation expert who specializes in helping businesses navigate the complex intersection of analytics, performance optimization, and marketing technology. With extensive experience in driving high-quality lead generation, she offers a critical perspective on the profound shifts happening in digital advertising as AI begins to reshape how consumers discover and interact with brands.
This conversation explores the competing visions for AI-powered advertising being pioneered by major tech players. We’ll examine how brands must adapt their creative strategies for conversational interfaces, the critical importance of structured data in this new ecosystem, and the fundamental changes to attribution and brand building. Ultimately, we’ll uncover the tactical shifts marketers need to make as the very nature of online discovery is redefined.
Some envision AI ads as sponsored, conversational responses rather than digital billboards. What specific creative strategies should marketers use to make sponsored content feel genuinely helpful, and what are the biggest risks to brand trust if the execution feels inauthentic?
The entire creative mindset has to shift from broadcasting a message to participating in a dialogue. Instead of designing a digital billboard, you’re crafting an expert recommendation that fits seamlessly into a conversation. The goal is for the ad to feel like a useful extension of the chat, not an interruption. For instance, if a user is asking about running shoes, the sponsored content shouldn’t just be a flashy ad; it needs to read like a helpful suggestion that mirrors the assistant’s tone and structure. The biggest risk is absolutely the erosion of trust. OpenAI seems acutely aware of this, emphasizing clear labeling and relevance. If these ads feel too invasive, too frequent, or just plain unhelpful, users will recoil. The entire model hinges on maintaining the user’s perception of the AI as a neutral, credible assistant.
Google is deeply integrating AI into its commerce ecosystem, from Search to YouTube. With AI Overviews potentially reducing click-throughs to websites, how should advertisers rethink attribution and visibility, and what new KPIs might become essential for measuring success?
This is the central challenge in Google’s new world. With AI Overviews already leading to more zero-click searches, the traditional model of measuring success by clicks to a landing page is becoming less reliable. Visibility is no longer just about ranking in the top ten blue links; it’s about being featured within the AI-generated summary itself. Google’s answer seems to be pulling the entire transaction deeper into its own ecosystem. They are creating tighter integrations between AI results and commerce units, making experiences shoppable directly within search and YouTube. For advertisers, this means attribution will become far more complex and modeled. We have to prepare for an increased reliance on AI-driven performance reporting and modeled conversions, where the platform tells you the value it generated, rather than tracking a simple, linear click-path.
AI discovery engines rely heavily on high-quality inputs. What are the most critical, immediate steps brands should take to optimize their structured data and product feeds for AI, and can you walk us through how superior data might lead to better placement in an AI-generated response?
The most critical step, without a doubt, is to treat your data as a primary marketing asset. This isn’t a long-term goal; it’s an immediate necessity. AI systems are only as good as the information they’re fed, so brands must focus on supplying rich, clean, and comprehensive structured data. This means meticulously organized product feeds with detailed attributes, clear hierarchies, and accurate information. Think of it this way: when an AI assistant is compiling an answer to “what’s the best accounting software for a small business,” it will pull from the data it can access and understand. A brand with a robust, well-structured feed providing clear information on features, pricing, and ideal customer profiles is far better positioned to be included as a relevant, authoritative option in that AI-generated response than a competitor with messy or incomplete data.
We’re seeing two distinct models emerge: one building native conversational ads from scratch, and another layering AI onto a mature ad infrastructure. What are the core trade-offs of each approach, and which model do you believe presents a greater long-term challenge for sustainable monetization?
These two models really represent two different philosophies. OpenAI is building native conversational placements from the ground up, which is a fascinating experiment. Their trade-off is balancing monetization with credibility; they have to invent a new ad format that users accept and find useful, all while avoiding the perception that their neutral assistant is for sale. Google, on the other hand, is layering AI onto its massive, decades-old advertising infrastructure. Their trade-off is managing the disruption to their existing model, specifically addressing advertiser concerns about how attribution and visibility will work when AI Overviews reduce website traffic. In the long term, I believe OpenAI faces the greater monetization challenge. They have to build a sustainable revenue stream from scratch and convince both users and advertisers that this new model works, whereas Google is evolving a deeply entrenched, multi-billion dollar system.
As AI assistants increasingly mediate how consumers find products and information, how does this change the fundamentals of brand building? Please explain the tactics required to build brand recognition and loyalty when the primary interface is a conversational AI, not a company website.
Brand building is shifting from creating a destination—your website—to becoming a trusted source that an AI would want to quote. The fundamentals change because you lose direct control over the user interface. The primary interface becomes the AI assistant itself, which is the new valuable real estate. To build a brand in this environment, tactics must focus on authority and data quality. Investing in original, authoritative content is paramount because it positions you as an expert source that an AI can reference. Simultaneously, optimizing your structured data ensures the AI has the correct, detailed information about your products and services. Brand loyalty will be built less through flashy web design and more through consistently being the most helpful, accurate, and relevant answer that the AI provides to a user’s query.
What is your forecast for AI in advertising?
My forecast is that we are witnessing the most significant structural shift since the dawn of search engines. The era of optimizing for “ten blue links” is fading rapidly, and the era of optimizing for AI-mediated discovery is accelerating. In the near future, the line between organic content and advertising will blur into “sponsored helpfulness.” Success won’t be about who has the biggest ad budget, but who provides the best, most structured data and authoritative content for AI engines to consume. The real battle won’t be for clicks, but for who owns the discovery interface—the initial point of contact for every consumer question and query. Marketers must prepare for both conversational and commerce-driven AI ecosystems, because the future of their brand’s visibility depends on it.
