I’m thrilled to sit down with Milena Traikovich, a seasoned Demand Gen expert who has helped countless businesses craft impactful campaigns to nurture high-quality leads. With her deep expertise in analytics, performance optimization, and lead generation, Milena is the perfect person to guide us through the evolving landscape of brand messaging in the age of generative AI. Today, we’ll explore how AI is reshaping brand narratives, the risks of losing control over your story, and actionable strategies to stay ahead of the curve. Let’s dive into this fascinating conversation about AI brand drift and its implications for businesses.
How would you describe “AI brand drift” in a way that’s easy for anyone to grasp?
AI brand drift is when the story or message about your brand, as told by AI systems, starts to stray from what you intended. Think of it like a game of telephone—AI pulls in bits and pieces from customer reviews, social media, or even leaked documents, and then spins a narrative that might not match your official voice. It’s a big deal because millions of people might see this altered version through search results or chatbots, and it can change how they perceive your company.
What do you see as the main reason AI is altering how consumers view brands today?
The core reason is that AI acts as a storyteller with access to a massive, unfiltered pool of data. It’s not just reading your press releases; it’s digesting every tweet, review, or forum post about your brand. Then, it synthesizes all of that into responses that sound authoritative. Consumers often trust these AI-generated summaries without questioning their accuracy, so the perception of your brand can shift overnight based on what the AI decides to highlight.
Can you explain how AI uses different sources of information to build a brand’s narrative?
Absolutely. AI doesn’t discriminate between sources—it grabs everything it can access online. That includes official stuff like your website and press kits, but also user-generated content like social media posts or memes, and even shadowy stuff like internal docs that might’ve slipped out. It mixes all these together to create a story. The problem is, if there’s negative sentiment in reviews or outdated info in a leaked file, that can weigh just as heavily as your polished marketing materials in shaping the narrative.
What’s the biggest danger for a company when AI starts telling a story that doesn’t align with their official message?
The biggest danger is losing trust and credibility. If AI spreads inaccuracies—like outdated product features or misquoted values—customers can get confused or frustrated, leading to support issues or even legal risks. Worse, if the drifted narrative goes viral through search results or chatbots, it can overshadow your official message for years, damaging your market position and making it incredibly hard to regain control.
Could you walk us through the four layers of the Brand Control Quadrant and why each is critical in the age of AI?
Sure, the Brand Control Quadrant breaks down how your brand exists across different layers, each feeding AI in unique ways. First, there’s the Known Brand—your logos, slogans, and official content. It’s the most controlled but just the surface. Then, the Latent Brand includes user-generated stuff like memes or community posts, which shapes how relatable AI sees your brand. The Shadow Brand is riskier—it’s internal or outdated content like old presentations that AI might unearth and use. Finally, the AI-Narrated Brand is how AI platforms describe you to the world, blending all layers into a version that users often accept as truth. Each layer matters because ignoring any one lets AI construct your story without your input.
How much control do companies actually have over their Known Brand layer when AI is in the picture?
Companies have a fair amount of control over the Known Brand layer since it’s their official assets—think websites, press kits, and brand guides. You can keep these updated and consistent. But here’s the catch: AI doesn’t just stop at your curated content. It contextualizes it with other layers, so even if your Known Brand is airtight, a negative review or a meme from the Latent layer can still influence how AI interprets and presents your message. Control is possible, but it’s not absolute.
What impact does the Latent Brand layer have on how AI portrays a company?
The Latent Brand layer—things like user-generated content, online discussions, and memes—has a huge impact because it reflects real-time public sentiment. AI uses this to gauge how relevant or relatable your brand is. If there’s a viral meme making fun of your product, AI might pick up that tone or context and weave it into its summaries, even if it’s not professional. It can make your brand seem less serious or authoritative, which might not align with your goals.
Why is the Shadow Brand layer such a tricky area for companies to manage?
The Shadow Brand layer is tricky because it includes stuff never meant for public eyes—like internal wikis, old slide decks, or onboarding docs. If these are online, even buried deep, AI can find and train on them. The risk is that this content is often outdated or off-message, so when AI pulls it into a response, it might share incorrect specs or reveal sensitive info. Most companies don’t even track their Shadow Brand, leaving them vulnerable to unexpected narrative twists.
Can you share an example of how factual drift in AI content could harm a company’s reputation?
Of course. Factual drift happens when AI starts with correct info but veers into inaccuracies. Imagine a tech company whose AI summary lists outdated features as current—say, a discontinued app integration. Customers might try to use it, get frustrated when it doesn’t work, and flood support with tickets. Worse, they might leave bad reviews or spread the word about a “broken” product. It’s a direct hit to reputation and can even lead to lost sales if trust erodes.
What’s your forecast for how AI will continue to shape brand narratives in the coming years?
I think AI’s role in shaping brand narratives will only grow, becoming a core part of how consumers discover and interact with companies. We’ll see even more reliance on AI-driven search and chatbots, which means the risk of brand drift will intensify unless companies adapt. I predict a surge in tools for monitoring and correcting AI narratives, alongside a push for marketers to actively manage all brand layers. Those who treat AI as a co-author of their story, rather than a passive tool, will stay ahead. Brands that ignore this shift risk losing their voice entirely to AI-generated distortions.
