Milena Traikovich stands at the intersection of high-stakes demand generation and clinical marketing analytics, having spent years steering brands through the turbulent waters of lead optimization and performance scaling. As the marketing landscape of 2026 grapples with the fallout of rapid technological adoption, she has become a leading voice for CMOs who find themselves caught between the board’s demand for AI-driven efficiency and the harsh reality of stagnant ROI. Her expertise isn’t just in the tools themselves, but in the structural and cultural shifts that occur when a company decides to pull its creative and media capabilities inside its own walls. In this conversation, we explore the historical echoes of previous in-housing movements and why the current “Third Wave” of AI integration is presenting an unprecedented accountability gap that could redefine the CMO role for the next decade.
The following discussion examines the cyclical nature of marketing operations, moving from the budget-saving desperation of the Great Recession to the trust-based shifts of the mid-2010s, and finally to our current era where generative tools promise speed but often lack a measurable impact on the bottom line. Milena breaks down the hidden costs of managing internal martech stacks, the cultural friction that often drives top creative talent back to agency life, and the sobering data from recent global surveys that show a massive disconnect between AI investment and business evidence.
Looking back at the major economic shifts of the last two decades, how have crises like the 2008 recession and the transparency issues of the mid-2010s fundamentally altered the way companies view the balance between internal teams and outside agencies?
When you look at the Great Recession of 2008 and 2009, the atmosphere in most marketing departments was one of pure survivalism, where every dollar spent was scrutinized under a microscope. Companies like Intel led the charge by pulling services, especially media, back in-house to preserve their dwindling budgets, effectively hiring creative talent to execute campaigns directly rather than paying the high premiums of external partners. It was a tactical move born of necessity, where the goal was to keep the lights on and the campaigns moving without the overhead of an agency’s profit margin. By the time we hit the mid-2010s digital boom, the motivation had shifted from simple cost-cutting to a profound crisis of trust and transparency, particularly surrounding social platforms and programmatic media. CMOs were losing sleep over whether their data was being handled correctly and if their partners were truly acting in their best interests, leading to a massive surge where the share of ANA members with in-house agencies jumped from 42% to 78% by 2018. These two periods taught us that while the reasons for moving in-house can change—from saving pennies to securing data—the impulse to reclaim control always resurfaces when the outside world feels too volatile or opaque.
You’ve mentioned that B2B brands often struggle to maintain a creative culture that can actually retain high-level talent; what is it about the “in-house” environment that makes it so difficult to keep creative minds engaged over the long term?
There is a specific, high-energy hum to agency life that is incredibly difficult to replicate within a single corporate brand, and that lack of variety often leads to what I call “creative stagnation.” In an agency, a creative professional might spend one week brainstorming a scrappy startup’s launch and the next week managing a total rebrand for a Fortune 500 giant, which provides a constant stream of new problems to solve and industries to learn. When that same talent moves in-house, they often find themselves trapped in a repetitive loop, becoming “order-takers” for a single brand identity that rarely changes, which can feel like a velvet cage for someone used to high-octane variety. We see a recurring pattern where top-tier talent is lured in by competitive salaries, only to drift back to the agency world within a year because they crave the diversity of work and the seat at the leadership table that internal departments often lack. Without that external spark and the ability to work across different sectors, the creative work can start to feel like a production line task rather than a strategic contribution, leading to a loss of the very brilliance the company hired them for in the first place.
When executives look at agency hourly rates, they often assume bringing work in-house will save millions, but what are the hidden financial realities of managing a modern martech stack that these leaders often overlook?
The math behind in-housing often looks great on a spreadsheet until you factor in the sheer weight of the infrastructure required to replace an agency’s capability. What many CMOs overlook is that an agency spreads the massive costs of software licenses, data platforms, and advanced martech stacks across a vast roster of clients, whereas an in-house team has to absorb those entire costs onto a single company’s balance sheet. It isn’t just about the salaries of the people sitting in the chairs; it’s about the millions of dollars in recurring technology fees and the constant need for specialized training to keep those tools running at peak performance. When you move from an outsourced model to an internal one, you aren’t just hiring creators; you are essentially starting a mini-technology firm within your marketing department, and the overhead can be staggering. We’ve seen many organizations realize too late that the “savings” they projected were actually just a relocation of costs from a service fee to a massive, internal capital expenditure that is much harder to cut when budgets get tight again.
We are currently navigating what you call the “Third Wave” of in-housing, powered by AI, but there seems to be a significant “performance gap” emerging—how are marketing leaders struggling to bridge the divide between tool adoption and actual business ROI?
The pressure from boards today is intense; they want to see AI integrated into every workflow because the efficiency case—making content faster and cheaper—is so easy to understand on the surface. However, the 2026 Duke University CMO Survey paints a very different picture, with marketing leaders rating their technology activities no higher than a 5 on a 7-point scale, and that includes their ability to generate actual ROI. This tells us that while the tools are definitely running and the content is being generated at an unprecedented scale, the proof of performance simply isn’t there to back up the investment. We are seeing a dangerous disconnect where the adoption of technology has outpaced the organization’s ability to turn those capabilities into measurable business results. It’s a situation where the “machine” is working perfectly, but the “output” isn’t moving the needle on the metrics that the board actually cares about, such as customer lifetime value or net new revenue.
With studies showing that a vast majority of organizations are seeing no measurable return from their massive GenAI investments, why has marketing become the “weakest link” in terms of providing evidence for this spend?
It is a bitter irony that sales and marketing absorbed the largest share of the $30 billion to $40 billion in enterprise GenAI investment precisely because their use cases were the easiest to explain to a board of directors. It’s very simple to pitch the idea of “faster emails” or “automated social posts,” but because these were the easiest low-hanging fruit, they were often implemented without the rigorous accountability structures that operations or finance pilots required. According to the GenAI Divide report by MIT NANDA, while 95% of organizations saw no measurable return, it was the less-funded operations and finance teams that actually produced better evidence of success because their goals were tied to concrete efficiency metrics from day one. Marketing, on the other hand, got the biggest slice of the pie but now finds itself in a position where 86% of leaders are being asked to justify that spending, while only a meager 16% feel they have the business evidence to do so. This creates a massive accountability gap where the most visible users of AI are also the ones least able to prove that their expensive new toys are actually making the company more money.
The lesson from previous in-housing movements seems to be that moving capabilities inside doesn’t solve fundamental problems of culture or cost; how does AI raise the stakes for CMOs who are trying to avoid repeating these historical mistakes?
AI doesn’t change the fundamental math of marketing leadership; it simply accelerates the speed at which a poorly planned strategy will fail. In 2008 and 2018, the failures were often about talent and trust, but in 2026, the failure is one of proof—if you can’t show that your internal AI-driven team is outperforming what an agency could do, you are just relocating the same inefficiencies to a more expensive, internal address. The stakes are higher now because the board has a direct eye on the technology spend, and they are starting to ask the CMO the exact same pointed questions about performance that the CMO used to ask their agencies. To avoid becoming a cautionary tale, leaders must solve for culture and total cost of ownership before they lean into the efficiency of AI, ensuring that their internal teams have the standing and the data to prove their value. Those who focus solely on the “how” of AI while ignoring the “why” of the business results are destined to see their internal departments dismantled just as quickly as they were built.
What is your forecast for the evolution of marketing accountability as we move further into this AI-integrated era?
My forecast is that we are entering a period of “brutal transparency” where the honeymoon phase of AI experimentation is officially over and every dollar spent on internal automation will be tied to a direct revenue outcome. We will see a significant shift away from “content volume” as a metric of success, as boards realize that generating 1,000 more blog posts or 10,000 more social ads doesn’t matter if they aren’t converting into high-quality leads. I expect that by late 2027, the gap between the 16% of CMOs who can prove their AI ROI and the rest of the field will lead to a massive turnover in marketing leadership, as companies look for “performance-first” executives who prioritize data over hype. The internal agency model will only survive if it can prove it is not just cheaper, but demonstrably more effective at driving growth than any external partner could ever be. Ultimately, the successful marketing leader of the future will be less of a creative director and more of a “revenue architect,” using AI as a precision tool rather than a blunt instrument for efficiency.
