Milena Traikovich has become a cornerstone of the demand generation community, known for her surgical precision in performance optimization and lead nurturing. As the digital landscape undergoes a radical shift toward algorithmic creation, her role has evolved into guiding brands through the murky waters of AI transparency and consumer trust. Her insights are not merely about checking boxes for compliance; they are about building a sustainable bridge between high-tech efficiency and the raw human authenticity that modern audiences crave. With years of experience managing complex campaigns, she understands that the “how” of marketing is now just as scrutinized as the “what.”
In this deep dive, we explore the nuances of the IAB’s latest disclosure guidelines and the delicate balance between informing the consumer and overwhelming them with unnecessary labels. We examine the stark reality of how transparency affects commercial performance, including significant drops in engagement when AI is mentioned. Furthermore, we discuss the varied global regulatory landscape that spans from New York to Seoul and why the younger generation’s indifference to AI-generated content might be the most surprising data point of all for brands striving to maintain a competitive edge.
With the IAB releasing its updated Transparency and Disclosure Framework, how do you personally draw the line between a standard digital touch-up and a synthetic experience that demands full transparency?
The distinction really lies in the materiality of the AI’s role and whether its presence fundamentally alters the consumer’s perception of reality. Under the updated IAB Framework Version 2, we are encouraged to take a risk-based approach, which means we aren’t just slapping a label on every pixel we adjust. When we utilize AI for synthetic videos, digital twins, or chatbots that could easily be mistaken for a living, breathing human, transparency is non-negotiable because those elements impact the core authenticity of the brand-to-consumer relationship. However, if we are talking about routine post-production, basic copy generation, or simple audio enhancements, the consensus is that disclosure isn’t currently required. It’s a delicate dance because, as IAB leadership points out, labeling every single minor enhancement would eventually teach consumers to tune out, leading to a dangerous “label fatigue” where they ignore the warnings that actually matter.
Looking at the demographic data, there is a fascinating split where 34% of younger audiences see AI as creative while 30% view it as inauthentic—how should brands navigate this cultural divide without alienating either group?
Navigating this divide requires a deep understanding of the Gen Z and Millennial psyche, where we see 73% of these cohorts admitting that AI disclosure has virtually no impact on their final purchase decision. This suggests a certain level of pragmatism; they care about the value of the product more than the tool used to sell it. Yet, the fact that 30% still perceive AI as inauthentic means there is a segment of the market that feels a sense of betrayal if they aren’t informed. We have to foster trust by being consistent, because while only 27% say they would be less likely to buy something based on AI use, that is still a significant chunk of revenue to leave on the table. We aim to honor that “creative” perception by using AI to push boundaries while maintaining the transparency necessary to ensure that the 30% who feel skeptical don’t feel like they are being tricked by a “synthetic” brand identity.
The NYU Stern study highlighting a 31.5% drop in click-through rates when AI use is disclosed is a sobering statistic for performance marketers. How can companies justify this commercial hit in the pursuit of transparency?
That 31.5% decline in click-through rates is a chilling figure that sends shivers through any performance-focused department, as it represents a tangible cost to being honest. However, we have to look at this through the lens of long-term brand equity versus short-term engagement metrics. If a brand uses AI to intentionally mislead audiences about representation or identity and gets caught without a label, the cost of that loss in trust will far exceed a temporary dip in clicks. The challenge is to find a middle ground where we avoid “over-disclosure” for low-risk uses that don’t benefit the audience. Advertisers are currently searching for that sweet spot, as only 17% believe AI should be disclosed every single time it’s used, despite 72% wanting clear industry standards to follow.
As regulations tighten from New York to Seoul, we’re seeing a fragmented global landscape of “sparkle” icons and mandatory text labels. How can global brands maintain a unified creative workflow under such diverse legal requirements?
Managing a global workflow in the current climate is a significant headache because the rules are shifting beneath our feet even as we speak. For instance, in New York, the synthetic performer law took effect this past June, while the EU’s Article 50 of the AI Act is being enforced starting this August. Meanwhile, South Korea moved early with its revised AI Basic Act back in January. In the US, we have the flexibility to choose between a subtle sparkle icon or a clear text label, but the EU has yet to mandate a specific icon, leaving us in a voluntary “Code of Practice” period. To stay ahead, brands must use the IAB framework as a baseline for a “global AI workflow” that can be localized at the final stage of delivery to meet specific jurisdictional thresholds.
What is your forecast for the future of AI transparency in digital advertising?
I believe we will see a shift toward “invisible but verifiable” transparency where the focus moves away from intrusive labels and toward a standard industry watermark that consumers can check if they choose. Currently, the industry is grappling with the fact that 72% of professionals want standards but resist blanket requirements, which tells me the market is desperate for a materiality-based system that doesn’t kill the “creative” spark that 34% of younger consumers enjoy. As adoption speeds up across every sector, the gap between what a machine can create and what a human can trust will become the most important metric we track. Eventually, the labels will likely become as commonplace and ignored as nutritional facts on food packaging, but until then, the brands that can balance disclosure without sacrificing the sensory appeal of their campaigns will be the ones that win the decade.
