I’m thrilled to sit down with Anastasia Braitsik, a global leader in SEO, content marketing, and data analytics. With her extensive expertise in the digital marketing landscape, Anastasia has been at the forefront of understanding how emerging technologies, especially artificial intelligence, are reshaping brand narratives. Today, we’ll dive into the fascinating and sometimes alarming world of AI brand drift—a phenomenon where AI-generated content can subtly or drastically alter how a brand is perceived. Our conversation will explore the layers of brand control, the risks of AI misrepresentation, and practical strategies for maintaining a consistent brand message in this AI-driven era.
How would you describe AI brand drift to someone who’s new to the concept, and why should companies care about it?
AI brand drift happens when the stories or messages about a company, generated by artificial intelligence, start to stray from what the company actually wants to say. Think of it like a game of telephone—AI pulls from all sorts of data like customer reviews, social media posts, or even leaked documents, and then spins out its own version of your brand story. Companies should care because these AI narratives can reach huge audiences through search results or chatbots, and if they’re off-base, they can confuse customers, damage trust, or even hurt your reputation overnight.
Can you break down the four layers of brand control—Known, Latent, Shadow, and AI-Narrated—and explain how they interact with AI systems?
Sure, these layers represent different aspects of how your brand exists in the digital world. The Known Brand is your official stuff—logos, slogans, press kits—the things you control directly. AI often uses these as a foundation but doesn’t stop there. The Latent Brand includes user-generated content like reviews or memes, which can shape how relatable or trendy AI sees your brand. The Shadow Brand is trickier—it’s internal or outdated material, like old presentations or internal docs, that AI might dig up and use, often incorrectly. Finally, the AI-Narrated Brand is how AI platforms summarize your brand to users, blending all these layers into a narrative that might not align with your vision. Each layer feeds into AI differently, and if you ignore any of them, you’re letting AI write your story without your input.
Which of these layers do you find most challenging for brands to manage, and what makes it so difficult?
I’d say the Shadow Brand is often the toughest. Most companies don’t even realize what’s out there—think old slide decks or internal wikis that accidentally got indexed online. These materials were never meant for public eyes, but AI doesn’t care. It can pull from them and present outdated or off-message info as fact. The challenge is tracking down these hidden assets and securing them, which requires constant audits and a level of digital housekeeping that many brands just aren’t prepared for.
How does the way AI generates content, without a clear plan for the whole output, contribute to brand messaging going off track?
AI, especially large language models, works by predicting the next word based on what’s come before, without an overarching strategy for the entire message. It’s like writing a story one sentence at a time without knowing the ending. This step-by-step approach means small errors or misinterpretations early on can snowball into bigger distortions. For instance, if AI starts with a slightly wrong fact or tone about your brand, it builds on that, leading to a narrative that’s way off from your intended message by the end.
What are some of the most significant risks a brand faces when AI misrepresents its message or values?
The risks are huge and multifaceted. First, there’s the loss of trust—when AI puts out a message that contradicts your values, customers might feel misled or betrayed. Then there’s the potential for misinformation, like listing features you don’t offer, which can frustrate users and flood your support team with complaints. Legally, you could face issues if AI misstates regulatory claims or exposes sensitive info. And don’t forget the reputational hit—once a distorted narrative spreads, especially via AI search summaries, it’s incredibly hard to correct the public’s perception.
Can you explain what zero-click risk means in the context of AI search summaries and why it’s such a concern for brands?
Zero-click risk refers to the situation where users get all their information from an AI-generated summary on a search engine, like Google’s AI Overviews, without ever clicking through to your official website. It’s a concern because if that summary is wrong or drifted from your true message, you’ve lost the chance to set the record straight. Your audience might never see your carefully crafted content, and you’ve got no direct touchpoint to correct misunderstandings or build a relationship with them.
What practical steps can a company take to spot AI brand drift early and prevent it from becoming a major issue?
The first step is monitoring. Regularly check how AI platforms describe your brand—search for your company on chatbots or AI-driven search tools and see what comes up. Next, build a strong foundation with your Known Brand by keeping official assets updated and clear, so AI has accurate data to pull from. Also, use social listening tools to track the Latent Brand—see what customers are saying in forums or on social media. Finally, audit your Shadow Brand to lock down or update any internal or outdated content that could leak into AI narratives. Catching drift early lets you correct it before it spirals.
What’s your forecast for how AI will continue to shape brand narratives in the coming years, and how should companies prepare for it?
I see AI becoming an even bigger player in how brands are perceived, especially as more people turn to AI tools for information over traditional search or direct website visits. We’ll likely see more sophisticated AI systems, but also more complex drift issues as they pull from an ever-growing pool of data. Companies need to prepare by making brand management a continuous, cross-functional effort—not just a marketing task. Invest in tools to track AI outputs, train teams to understand these layers of brand control, and prioritize creating a strong, consistent digital presence. Staying proactive is the only way to keep your narrative in check as AI evolves.
