I’m thrilled to sit down with Milena Traikovich, a powerhouse in the realm of demand generation. With her deep expertise in analytics, performance optimization, and lead generation, Milena has guided countless businesses in crafting campaigns that not only attract but also nurture high-quality leads. Today, we’re diving into the transformative world of AI in marketing, exploring how it’s reshaping the marketer’s role, redefining personalization, and altering the dynamics between brands and consumers during this pivotal platform shift.
How would you describe the concept of a “platform shift” when it comes to AI in marketing?
A platform shift in the context of AI refers to a fundamental change in the technological foundation that marketers rely on to connect with consumers. Unlike previous shifts—say, from desktop to mobile—this one is driven by AI’s unique, unpredictable nature. It’s not just about adopting a new tool; it’s about rethinking how we operate as AI redefines data processing, decision-making, and customer engagement at a scale and speed we’ve never seen before. This shift is shaking up the very infrastructure of marketing, pushing us to adapt in ways we can’t fully predict yet.
Why do you think it’s so challenging to forecast where AI will take marketing in the next few years compared to earlier tech evolutions?
Unlike past tech changes, where you could often see a linear progression—like more powerful computers or faster internet—AI operates with non-deterministic properties. Its ability to learn, adapt, and sometimes surprise us with outcomes makes it hard to map out a clear trajectory. We’re dealing with systems that evolve based on data and interactions in real time, so trying to predict where AI will be even a year from now feels like guesswork. It requires us to think from first principles and stay ready for unexpected leaps rather than relying on past patterns.
How do you see this AI-driven shift changing the relationship between marketers and their audiences?
At its core, the relationship stays the same—consumers want value, and marketers want to deliver it. But AI is transforming how that connection happens. It’s enabling a level of personalization and responsiveness that wasn’t possible before, allowing marketers to meet consumers exactly where they are with tailored experiences. This shift could deepen trust if done right, as customers feel understood, but it also raises expectations. Marketers will need to use AI ethically and transparently to maintain that bond, or risk alienating their audience with overreach.
In what ways is AI already altering the daily responsibilities of marketers?
Right now, AI is taking over a lot of the grunt work—things like drafting initial content, segmenting audiences, or scheduling campaigns. I’ve seen teams cut down hours of manual data crunching by using AI to analyze performance metrics in seconds. This frees up marketers to focus on the bigger picture, like crafting unique campaign ideas or diving deeper into customer insights. It’s less about repetitive tasks and more about steering the ship with better tools at hand.
As AI handles more of these routine tasks, what kind of creative or strategic priorities do you think marketers should lean into?
With AI managing the mundane, marketers can double down on creativity and strategy. This means brainstorming bold, innovative campaigns that stand out in a crowded space or diving into nuanced testing to refine messaging. It’s also a chance to focus on storytelling—building emotional connections that AI can’t replicate on its own. Strategically, marketers can spend more time aligning campaigns with long-term brand goals and experimenting with new ways to engage audiences, knowing the operational heavy lifting is covered.
What steps can marketers take to ensure they’re ready to manage AI tools effectively in the long run?
First, they need to invest in learning—not just how to use AI tools, but how to think alongside them. This means understanding the basics of data inputs and outputs so you can spot when AI is off track. Building a culture of adaptability is key; marketers should regularly upskill through workshops or certifications as AI evolves. Also, focusing on managing AI as a resource—setting clear goals and guardrails—will help ensure it’s a partner, not a crutch, over time.
Can you paint a picture of what it looks like for AI to function as a teammate in a marketing setting?
Imagine AI as a set of digital colleagues, each with a specific role. You might have one AI agent personalizing email content based on user behavior, another ensuring every message aligns with your brand voice, and a third flagging underperforming campaigns in real time. As a marketer, you’re the manager, setting the objectives and reviewing the output. It’s practical collaboration—AI handles the heavy data lifting, while you bring the human judgment and creative spark to guide the overall effort.
Could you share an example of how multiple AI agents might collaborate to enhance a marketing campaign?
Sure, let’s say you’re launching a product re-engagement campaign. One AI agent could analyze customer data to identify users at risk of churning, suggesting personalized product recommendations. Another agent might test different message formats to ensure they’re polished and on-brand, while a third determines the best delivery channel and timing based on past interactions. A fourth could monitor performance and alert you if open rates drop. Together, these agents streamline the campaign, making it more targeted and efficient without you micromanaging every step.
How do you envision AI decisioning taking personalization beyond what traditional methods could achieve?
Traditional personalization often relied on static segments—like targeting “millennials” with a specific offer. AI decisioning, on the other hand, uses reinforcement learning to adapt in real time based on individual behavior. It doesn’t just group people; it learns what each person responds to, optimizing for outcomes like clicks or purchases on a 1:1 level. This means a customer might get a unique offer, delivered at the perfect time on their preferred channel, something pre-set rules or manual efforts could never scale to.
Why is achieving true 1:1 engagement so crucial for customer experiences, and how does AI make it a reality?
True 1:1 engagement matters because it makes customers feel seen as individuals, not just part of a crowd. That relevance builds loyalty and drives better results—think higher conversions or repeat purchases. AI makes this possible by processing vast amounts of first-party data instantly, learning from every interaction to tailor the next one. It can figure out not just what a customer might like, but when and how they want to hear about it, creating experiences that feel personal at a scale humans alone couldn’t manage.
Looking ahead, what’s your forecast for how AI will continue to shape customer engagement in the coming years?
I believe AI will push customer engagement into even more dynamic, predictive territory. We’ll see it not just reacting to behavior but anticipating needs before customers even express them, using deeper insights from integrated data sources. Engagement will become seamless across channels, with AI orchestrating a unified experience whether someone’s on social media, email, or in-store. The challenge will be balancing this power with privacy and trust, but if done right, AI could make every interaction feel like a conversation with a trusted friend.
