Allow me to introduce Milena Traikovich, a seasoned expert in demand generation who has been transforming the way businesses nurture high-quality leads through innovative campaigns. With a deep background in analytics, performance optimization, and lead generation, Milena has also embraced cutting-edge tools like Generative AI (GenAI) to revolutionize content creation. In this engaging conversation, we dive into her journey with GenAI, exploring how it has reshaped efficiency, creativity, and strategy in digital content. We’ll touch on the incredible opportunities it offers, the challenges of maintaining brand authenticity, and the ethical considerations that come with leveraging such powerful technology.
How did you first get drawn into using Generative AI for content creation, and what challenges in traditional methods nudged you toward it?
Honestly, I stumbled into GenAI out of necessity. Traditional content creation was often a slog—hours of brainstorming, drafting, and editing, especially for high-volume campaigns. I was constantly looking for ways to streamline repetitive tasks without sacrificing quality. A few years back, I noticed the buzz around AI tools and decided to experiment with platforms that promised to generate text quickly. The tipping point was a project with a tight deadline where we needed dozens of social media posts in a day. GenAI delivered drafts in minutes, and while they needed polishing, it was a game-changer. It felt like having an extra team member who never slept.
Can you share how GenAI has impacted the speed of your content production, and maybe an example of a project that benefited from it?
The speed impact is unreal. What used to take days can now be done in hours, sometimes minutes. For instance, I worked on a blog series for a client last year—normally, drafting five 800-word posts would’ve taken a week with research and writing. Using GenAI, I had rough drafts in under an hour per post. It gave me time to focus on refining the tone and adding data-driven insights, which made the final product much stronger. The client was thrilled with both the turnaround and the quality.
When it comes to different content types like blogs, ads, or social media, how do you typically apply GenAI, and which area do you find it most useful for?
I use GenAI across the board, but it shines in different ways depending on the content. For blogs, it’s great for outlines and first drafts, especially on technical topics where it pulls together a solid base to build on. With ads, I love how it generates multiple variations of copy in seconds—I can test ten taglines and pick the best. Social media is probably where I find it most useful, though. Crafting captions and hashtags for daily posts across platforms is tedious, but GenAI churns out engaging ideas fast, keeping the momentum going without burning out my team.
How do you ensure that AI-generated content aligns with a brand’s unique voice and doesn’t come off as too generic?
That’s a big priority for me. GenAI can be a bit cookie-cutter if you don’t guide it properly. I start by feeding it detailed prompts with specifics about the brand’s tone—whether it’s witty, professional, or conversational—and examples of past content. Even then, I spend time tweaking the output to make sure it feels authentic. I’ve had moments where the AI spits out something that’s just too bland or off-mark, like a social post that sounded like a corporate memo. It’s a reminder that human oversight is key to keeping that personal touch.
What’s been your experience with the cost savings of using GenAI, and do you think they outweigh any occasional drawbacks?
The cost savings are significant, especially for smaller businesses or startups I work with. I’ve been able to reduce the need for extra freelance writers on projects with tight budgets by using AI for initial drafts or bulk content. That said, there are hiccups—sometimes the AI misses the mark, and I have to invest time in edits. But overall, the savings in time and resources far outweigh those minor issues. It’s about striking a balance and knowing when to lean on AI versus human talent.
How do you manage the risk of errors or inaccuracies in AI-generated content before it reaches your audience?
I’m super cautious about this because credibility is everything. I’ve set up a strict review process where every piece of AI-generated content gets fact-checked and cross-referenced by a human. I also double-check stats, dates, and claims, since AI can sometimes pull outdated or flat-out wrong info. I had a near-miss once with a blog post where the AI cited a statistic that sounded plausible but was completely fabricated. Thankfully, we caught it during editing, but it reinforced why vigilance is non-negotiable.
What are your thoughts on the ethical challenges of using GenAI, such as the potential for misinformation or biased outputs?
It’s a real concern, and I think anyone using GenAI needs to approach it with responsibility. Misinformation can spread like wildfire, and biased content can alienate or mislead audiences. I make it a point to scrutinize outputs for any unintended slant and ensure they align with factual, inclusive messaging. Beyond that, transparency matters— if AI plays a big role in content, I’m upfront about it, especially for sensitive topics. It’s about building trust with your audience while harnessing the tech’s benefits.
Looking ahead, what is your forecast for the role of GenAI in content creation over the next few years?
I think GenAI is only going to become more integrated into creative workflows, evolving to produce even more nuanced and context-aware content. We’ll likely see tools that better understand emotional tone and cultural nuances, making outputs feel more human. I also expect hybrid approaches to dominate—AI handling the heavy lifting of scale and speed, while humans focus on storytelling and authenticity. The challenge will be ensuring ethical boundaries keep pace with innovation, but I’m optimistic that businesses adopting GenAI thoughtfully will redefine how we connect with audiences.
