In the rapidly evolving world of marketing technology, few professionals are as insightful as Milena Traikovich, a Demand Gen expert who has dedicated her career to helping businesses craft impactful campaigns that nurture high-quality leads. With her deep expertise in analytics, performance optimization, and lead generation, Milena offers a unique perspective on how AI is reshaping the marketing landscape. In this interview, we explore the transformative role of AI in amplifying creativity, the rise of the full-stack marketer, the challenges of balancing speed with authenticity, and the global differences in AI adoption, among other critical topics. Join us as we dive into her thoughts on how marketers can harness technology while keeping the human touch at the forefront.
How did you first come to see AI as a tool that enhances creativity in marketing rather than replacing it?
I started noticing this trend a few years ago when I saw how AI could take repetitive tasks off marketers’ plates, giving them more space to think outside the box. Instead of just churning out content, AI helps by providing insights and ideas that spark inspiration. For instance, I’ve seen teams use AI to analyze audience sentiment in real time, which then fuels brainstorming sessions for campaigns that resonate on a deeper level. It’s not about AI doing the creative work; it’s about amplifying what humans already bring to the table by clearing the way for bigger, bolder ideas.
Can you share some specific examples where AI has acted as a catalyst for creative marketing ideas?
Absolutely. One example that stands out is a campaign I worked on where we used AI to sift through massive amounts of social media data to identify trending topics and emotions among our target audience. The tool flagged a niche interest we hadn’t considered, which led to a quirky, highly engaging video series that went viral. Without AI pointing us in that direction, we might have missed the opportunity. Another case is using generative tools to mock up dozens of ad visuals in minutes, allowing the team to pick and refine the best concepts rather than starting from scratch. It’s like having a creative partner that never runs out of steam.
What does the idea of ‘evidence-based creativity’ mean to you, and how does it play out in modern marketing?
Evidence-based creativity is all about blending human intuition with hard data from AI tools to make smarter, more impactful decisions. It means you’re not just guessing what will work; you’re using AI to test hypotheses, predict outcomes, and validate ideas before they go live. For example, marketers can use AI to analyze past campaign performance and pair those insights with their gut feel for storytelling to craft messages that hit the mark. It’s a game-changer because it reduces risk while still leaving room for that human spark that makes a campaign memorable.
Why do you think skills like data analysis and personalization are becoming so essential for marketers today?
The marketing world is more competitive and data-driven than ever. Customers expect experiences tailored to their needs, and that’s where personalization comes in—it’s no longer a nice-to-have, it’s a must. Data analysis is critical because it helps us understand what drives behavior, segment audiences effectively, and measure impact in real time. Without these skills, marketers risk falling behind as campaigns become more complex and tech-heavy. Knowing how to interpret data and apply it to personalize content at scale is what separates good marketers from great ones in today’s landscape.
How would you define a ‘full-stack marketer,’ and what does this role look like in practice?
A full-stack marketer is someone who’s comfortable across the entire spectrum of marketing—from creative ideation to tech implementation. They can write compelling copy, analyze performance metrics, and navigate AI tools or tech stacks with ease. In practice, this looks like someone who can draft a campaign strategy, use AI to optimize content for different platforms, and then dive into the analytics to see what’s working. It’s about versatility and being able to connect the dots between art and science to deliver results.
What role do AI tools play in a full-stack marketer’s daily workflow?
AI tools are like a trusted sidekick for full-stack marketers. They streamline mundane tasks and supercharge efficiency. For instance, AI copilots in productivity software can help draft emails or brainstorm ideas, while generative tools can whip up content variations for testing. I’ve seen marketers use these tools to cut down localization time for global campaigns from weeks to hours. This frees them up to focus on strategy and ensuring the content aligns with the brand’s voice. AI isn’t just a tool; it’s a force multiplier that lets marketers do more with less.
How can marketing leaders ensure that human creativity and authenticity remain central when using AI?
It starts with setting clear boundaries and processes. Leaders need to make sure humans are always in the loop, especially for decisions about tone, quality, and cultural relevance. This means using AI for efficiency—say, generating drafts or analyzing data—but having team members review and refine the output to match the brand’s unique voice. Training teams to see AI as a collaborator, not a replacement, is key. It’s also about fostering a culture where creativity is celebrated, so people feel empowered to bring their personal insights and experiences to the table, even with tech in the mix.
What do you think is the biggest hurdle causing the ‘optimism-execution gap’ in AI adoption among marketing teams?
The biggest hurdle is the uncertainty around ROI. Many leaders are excited about AI’s potential, but they struggle to justify big investments when the results aren’t immediately clear. There’s also a learning curve—figuring out how to integrate AI into existing workflows without disrupting everything takes time and resources. I’ve seen teams get stuck in the pilot phase because they’re afraid to scale up without a proven formula. It’s a mix of caution and the challenge of aligning AI with measurable business outcomes that keeps many from fully committing.
How can organizations move from just experimenting with AI to truly integrating it into their workflows?
It’s about shifting from ad-hoc testing to a structured approach. Organizations need to define clear goals for AI—whether it’s speeding up content creation or improving personalization—and then build it into their processes with specific roles and guardrails. Start small with high-impact areas like automating repetitive tasks, then scale up as teams gain confidence. It’s also crucial to invest in training so everyone understands how to use the tools effectively. Finally, focus on measurement. Set KPIs early on to track progress and show value, which helps build momentum for broader adoption.
What is your forecast for the future of AI in marketing over the next five years?
I believe AI will become even more embedded in marketing, to the point where it’s just part of the fabric of how we work, much like social media is today. We’ll see smarter, more intuitive tools that anticipate marketers’ needs and offer real-time suggestions. Personalization will reach new heights as AI gets better at understanding context and emotion. However, I also think the human element will remain irreplaceable—AI will handle the heavy lifting, but creativity, empathy, and cultural nuance will still come from people. My hope is that this balance drives a new era of marketing that’s both incredibly efficient and deeply human.
