I’m thrilled to sit down with Milena Traikovich, a seasoned expert in demand generation 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 strategies, Milena offers a unique perspective on how AI is transforming the marketing and sales landscape. In our conversation, we dive into the rapid adoption of AI tools and agents among professionals, the surprising ways these technologies are being used, the critical gap in role-specific training, and the risks that come with unapproved tool usage. We also explore what better training could look like and how it could unlock AI’s full potential for teams.
How widespread do you see AI adoption in marketing and sales teams right now, and are there specific industries or regions where it’s particularly strong?
From what I’ve seen, AI adoption in marketing and sales is incredibly widespread, with a majority of professionals integrating it into their workflows. I’d say around two-thirds or more are using AI in some capacity, based on recent surveys and my own interactions with clients. The UK seems to be leading the charge, with adoption rates reportedly higher than in the US. Industry-wise, professional services stand out—most teams in that sector are leveraging AI for everything from analytics to client outreach. It’s exciting to see how quickly it’s becoming a staple.
What are some of the most common tasks that marketing and sales teams are turning to AI for, and have you noticed any unexpected applications?
The most common tasks are definitely content creation, market research, and sales operations—think drafting emails, generating reports, or analyzing customer data. A lot of teams also use AI for customer relationship management and advertising. What’s caught me off guard is how some are using it for niche things like event planning support or even fine-tuning social media tone based on audience sentiment. It’s fascinating to see AI pop up in areas you wouldn’t traditionally expect, showing just how versatile it can be.
Can you break down the difference between basic AI tools and AI agents in the context of marketing and sales, and how are agents changing the game?
Sure, basic AI tools are typically designed for specific, often single-step tasks—like generating a piece of content or pulling a data insight. AI agents, on the other hand, are more autonomous. They can handle multi-step processes without constant human input, like qualifying leads, drafting follow-up emails, and even scheduling outreach. I’ve seen a growing number of professionals—over half in some studies—relying on these agents, and the impact is huge. They’re freeing up time for strategic thinking and reducing the grind of repetitive tasks, which is a game-changer for productivity.
With only a small percentage of professionals receiving role-specific AI training, what do you think is holding back more tailored education in this space?
The training gap is a real issue, with only about 17% getting training that fits their specific job needs. I think the main hurdle is that companies are still catching up to how fast AI is evolving. Many are either offering generic courses that don’t dive into marketing or sales nuances, or they’re not prioritizing training at all—about a third of professionals have had none. There’s also a resource issue; creating customized programs takes time and expertise that not every organization has. It’s a missed opportunity because tailored training could make a massive difference in effectiveness.
What kind of training do marketing and sales professionals typically receive, and how can it be made more relevant to their day-to-day roles?
Most training right now is either too broad—covering general AI concepts without practical application—or purely theoretical, lacking hands-on examples. I’ve heard from many professionals that they’ve had to seek out their own resources or just learn on the job. To make it more relevant, training needs to focus on real-world scenarios, like how to use AI for segmenting audiences or optimizing ad spend. Interactive workshops or case studies specific to their industry would go a long way in bridging that gap and making the learning stick.
There’s a significant number of professionals using unapproved AI tools. What risks does this pose for companies, and why do you think this is happening?
Using unapproved tools is a big concern—almost half of professionals admit to it. The risks are serious: data breaches, compliance violations, and even brand safety issues if the tool outputs something off-message. I think it’s happening because there’s often a lack of clear guidelines or accessible company-approved options. People are eager to get results, so they turn to whatever’s available, like free public platforms. Without proper governance, it’s a bit of a Wild West, and companies need to step up with policies and approved tools to mitigate these dangers.
What do professionals seem to want most from AI training programs, and how important is keeping that training current?
From what I’ve gathered, professionals are craving practical, self-paced options like online modules with industry-specific examples. They want workshops where they can test AI in simulated campaigns or learn from peers facing similar challenges. Keeping training current is absolutely critical—AI evolves so fast that a course from even a year ago might be outdated. Regular updates ensure users are equipped to handle new features or risks, and it builds confidence in using the technology effectively over time.
Looking ahead, what’s your forecast for how AI will continue to shape marketing and sales in the coming years?
I think we’re just scratching the surface. In the next few years, AI will become even more integrated, especially with agents taking on complex, end-to-end processes like full campaign management or predictive customer behavior modeling. Personalization will hit new levels, with AI tailoring experiences in real-time based on incredibly nuanced data. But the flip side is that training and governance will need to keep pace to avoid pitfalls. I’m optimistic we’ll see a shift toward more strategic roles for humans, with AI handling the heavy lifting, as long as we address the skills gap head-on.
