Milena Traikovich is a powerhouse in demand generation, known for turning stagnant lead funnels into high-performance engines. With a deep background in analytics and performance optimization, she understands that the “more is better” philosophy—whether it’s more people or more AI—is a trap if the foundation isn’t solid. Today, she shares her insights on why marketing leaders are struggling to scale and how to identify the invisible barriers holding teams back in this fast-evolving landscape.
When a marketing team finds itself struggling to meet output goals, how do you distinguish between a fundamental lack of technical proficiency and a genuine need for more headcount?
Distinguishing between these two requires looking past the sheer volume of work and focusing on the nature of the friction. A skills gap is essentially the distance between what the work requires and what your team can actually produce with their current toolset. For instance, I often see teams that have mastered basic email scheduling but are completely lost when it comes to more advanced tasks like behavioral scoring. If your team is hitting a wall because the tech stack has evolved faster than their training, adding more people will only result in those new hires adopting the same inefficient workarounds. On the other hand, a headcount gap is purely a matter of hours in the day; it’s when a team knows exactly how to execute at high quality, but they are physically capped. If a team is running 12 campaigns perfectly but the business plan demands 40, no amount of training will close that gap because you simply lack the program managers and analysts to handle the volume. It is a frustrating realization for many CMOs, but hiring into a team that lacks skills is just paying more to produce the wrong work faster.
AI is frequently sold as a solution for both labor shortages and skill deficits, but how does its implementation actually affect these two very different types of gaps in the current market?
AI is a double-edged sword because it is marketed as both a specialized analyst and an extra pair of hands, which muddies the strategic waters for leadership. In our current 2026 landscape, we are seeing labor’s share of the marketing budget actually rise to 24.5%, up from 21.9% last year, which suggests that CMOs aren’t viewing AI as a replacement for human talent. The reality is that the top barrier to AI-driven efficiency for 38% of organizations is a blatant lack of internal AI expertise. If you drop AI on top of a skills gap, you don’t solve the problem; you just create a new, exhausting job: checking the machine’s work. As the industry has noted, AI is not a shortcut around marketing capability, and without that foundational skill, the output remains unreliable. When a skilled team uses AI, they can leverage it to take over volume, but when an unskilled team uses it, they often find themselves buried under even more drafts that still require expert intervention to be usable.
With a significant majority of marketing leaders spending hours every week correcting AI output, what does this tell us about the hidden human cost of automation?
The human cost is much higher than most executive boards are willing to admit, and the sensory reality of this is a team that feels like they are constantly “fixing” rather than “creating.” A recent study found that 76% of marketing leaders are spending at least three hours every single week editing, fact-checking, or correcting what the AI produces. This is a massive drain on morale, especially when 54% of these leaders report that their own leadership completely underestimates the human effort required to make AI output usable for the brand. It creates a paradox where 39% of marketers say they are now too busy managing these automated workflows to actually think strategically about the business. There is also a deep-seated anxiety regarding the next generation, with 46% of leaders worrying that heavy AI use will erode the development of junior marketers. If the tool is doing the “first draft” work that junior staff used to learn from, we risk creating a future where no one has the foundational skills to even know what a “good” segment or a “bad” brand claim looks like.
What specific diagnostic steps can a leader take to pinpoint whether their team is running out of hours or simply running out of expertise before they commit to a new budget?
I recommend three specific checks that provide immediate clarity and save organizations from wasting thousands of dollars on the wrong fix. First, look at exactly what is being corrected in the review process; if the fixes are about judgment—like targeting the wrong audience or making an off-brand claim—that is a skill issue, whereas typos and missed deadlines usually point to a headcount issue. Second, identify where the work is waiting; if projects are bottlenecked at the desk of the one person who knows how to build a complex audience, you have a concentrated skills gap that is also a major headcount risk if that person ever leaves. Finally, I suggest the “subtraction test,” where you pull one recurring project off the team’s plate for a full month. If the quality of their other work improves significantly, they were short on hours, but if the output remains mediocre despite the extra time, you are looking at a fundamental skill deficit. This test costs you one month of one project, but it prevents you from making a permanent, six-figure hiring mistake.
If a team is suffering from both a skills gap and a headcount gap, why do you advocate for prioritizing skills first, and what does a “skills hire” look like in practice?
When you have both gaps, fixing skills first is the only logical path because a skills gap actually masquerades as a headcount gap by burning hours on rework and inefficient workarounds. By training the team to do the work correctly the first time, you often find that a portion of your “staffing” problem simply disappears. This is a difficult transition because it often means missing some of this year’s output goals to ensure you can hit next year’s targets, but the alternative is a perpetual cycle of low-quality volume. A “skills hire” is a strategic move where your next headcount isn’t just another pair of hands, but an experienced professional whose explicit job description includes teaching the existing team. This person acts as a force multiplier, providing an extra pair of hands today while ensuring the entire team is better trained and more autonomous six months from now. Given that 56% of CMOs report they lack the budget to deliver their 2026 strategy, this kind of internal development is often the only sustainable way to grow.
How should marketing leaders be rethinking their budget allocations to ensure that new technology investments actually deliver the efficiency they promise?
We have to stop treating the software license as the total cost of ownership and start budgeting for the human intelligence required to run it. I always tell my clients to follow the 15% to 20% rule: if you are spending $100,000 on a new AI or martech license, you must have a separate line item for $15,000 to $20,000 dedicated strictly to training. Furthermore, the ratio of operations to platforms is non-negotiable; you generally need one dedicated process and operations role for every three to four core platforms you maintain. Without this investment in people and process, the technology becomes shelfware or, worse, an expensive way to produce more noise. Before any AI request goes to the finance department, it needs to explicitly state which gap it is closing—skills or people—and provide the data to prove it.
What is your forecast for the evolution of marketing operations?
I believe we are entering a period of “capability-driven growth” where the most successful organizations will be those that stop chasing raw output volume and start focusing on the depth of their team’s technical and strategic expertise. As the 54% of leaders reporting insufficient resources can attest, we can no longer outspend our inefficiencies. The future belongs to the lean, highly-skilled teams who use AI as a high-precision tool rather than a crutch for a lack of talent. We will see a shift where the “checker” role becomes the most senior position in the department, requiring an intuitive understanding of brand, strategy, and data that no machine can replicate. Organizations that invest in closing their skills gap today will find themselves with a massive competitive advantage as they will finally be able to realize the efficiency gains that everyone else is only dreaming about.
