Short introduction Meet Milena Traikovich, a powerhouse in the realm of demand generation who has dedicated her career to helping businesses craft campaigns that attract and nurture high-quality leads. With her deep expertise in analytics, performance optimization, and lead generation strategies, Milena is at the forefront of navigating the seismic shifts in digital content strategy. In this interview, we dive into the evolving landscape of the web, exploring how AI is rewriting the rules of content consumption, why traditional strategies are faltering, and the innovative concept of a dual web designed for both humans and machines. We also unpack the risks of AI misrepresentation and the untapped potential for those who adapt early to this new reality.
How do you see the web fundamentally changing in recent times, and what’s driving this transformation?
The web as we’ve known it for the past couple of decades is undergoing a radical shift, and honestly, it’s like it hit a wall last week without most of us even noticing. The core driver is AI and how it consumes content. Unlike humans, AI doesn’t care about the flashy designs or clever wordplay we’ve spent years perfecting. It’s all about raw data, structure, and clarity. This isn’t just a tweak to the system; it’s a complete rethinking of how information is processed and delivered, and it’s happening faster than any of us expected.
What makes traditional strategies like SEO fall short in this AI-driven environment?
SEO, as we’ve practiced it for years, was built for human search behaviors and older algorithms that prioritized keywords and backlinks. But AI doesn’t think like a human searcher. It’s not swayed by catchy headlines or keyword stuffing—those can actually backfire now by making content seem noisy or irrelevant. AI craves structured, factual data it can parse without guesswork. Old tactics that focused on gaming the system are becoming liabilities because they don’t align with how machines interpret and rank content today.
Can you explain why a web built for humans often feels ‘hostile’ to machines?
Absolutely. The web we’ve designed is all about human experience—think beautiful visuals, immersive storytelling, and interactive elements like parallax scrolling. While these resonate with people, they’re often invisible or confusing to AI. Machines don’t ‘see’ design flair; they scan the underlying code for clear signals. So, a gorgeous website might be a masterpiece to us, but to AI, it’s just a jumble of meaningless HTML if it lacks structure or machine-readable markers like schema markup.
What is the ‘dual web’ concept, and why do you believe it’s the way forward?
The dual web is about recognizing that humans and machines need entirely different versions of content. It’s not enough to tweak a single site to be ‘accessible’ to both. Humans want emotion, creativity, and engagement—think vibrant brand stories. Machines, on the other hand, demand pure signal: structured data, clear hierarchies, and no fluff. The dual web means building two parallel experiences—one for each audience—because trying to mash them together just dilutes the effectiveness for both.
How do you approach creating content that’s optimized for machines without losing the human touch?
It’s a balancing act. For machines, the focus is on elements like structured data, semantic clarity, and plain-text summaries that AI can easily parse. Think of it as giving AI a clear roadmap to your content. But for humans, you still need that emotional pull—stories, visuals, and personality. The trick is maintaining a human-centric site that’s rich and engaging while serving a stripped-down, machine-friendly version alongside it. It’s about ensuring neither audience feels shortchanged.
What are some of the real-world risks for brands when AI misinterprets or misrepresents their content?
The risks are huge and often underestimated. When AI can’t parse your content properly, it doesn’t just ignore you—it fills in the blanks with whatever it can find, like outdated info from a competitor’s site or a poorly written Wikipedia stub. Imagine a customer asking AI about your pricing, and it quotes something from five years ago because your site wasn’t clear. That’s not just a missed opportunity; it’s a direct hit to your credibility and could drive business straight to someone else.
Can you elaborate on the ‘first-mover advantage’ in adopting a dual web strategy?
Being an early adopter of a dual web approach isn’t just about avoiding problems—it’s about shaping the narrative. AI systems are increasingly how people discover information, and they prioritize content that’s easy to understand and cite. If you’re the first in your industry to build a machine-optimized presence, you’re more likely to be the go-to source when AI answers questions about your field. That’s a powerful position to hold, as it lets you define how your brand and even your entire category are perceived.
What’s your forecast for the future of digital content strategy in this AI-dominated landscape?
I see the divide between human and machine needs growing even sharper over the next few years. The dual web will become the standard, not the exception, as more businesses realize they can’t afford to be invisible or misrepresented by AI. We’ll also see new tools and standards emerge to help manage this split—think protocols for controlling how AI accesses content, similar to what robots.txt did for crawlers. Ultimately, the winners will be those who embrace this duality early, balancing human engagement with machine precision to stay relevant in a world where AI is often the first point of contact.
