As AI seeps into many facets of our lives, there have been glimpses of a potential utopia for knowledge workers (putting aside all of the second and third-order effects for a moment). A tedious task that used to take an entire day can now take 30 minutes of collaboration with the chatbot of your choice, and we’re freed up to move onto bigger and more interesting things.
In this edition of How AI Will Change..., we spoke with Alena Morris, VP of Product Marketing at Kargo, about how AI has the potential to free up media planners and strategists to discover and innovate. During her 15 years in ad tech and media, she led product marketing across publisher, DSP, and SSP roles, driving transformation initiatives, from SSP-to-buy-side expansion and retail media launches to AI-powered buying and creative.
GenAI can democratize creative. You no longer need massive budgets to produce high-quality, innovative ads—think video for CTV, rapid iteration, repurposing assets at scale. It can supercharge creativity and reduce manual work. That said, the human element still matters. We’ve already seen consumer backlash when creative feels synthetic—no emotion, no honesty. Our teams, and many brands we speak with (pharma, tech, etc.), see AI as fantastic for brainstorming and acceleration, while designers still craft the final imagery. The other big unlock is detailed insights on creative performance. AI can digest performance data such as themes, fonts, colors, messages and surface what actually works by brand, vertical, and season. Historically, strategists and planners didn’t have access to that level of feedback. Bringing those insights to creative teams is powerful.
Exactly. There’s a stat that ~47% of campaign performance comes from creative. Using AI to mine what’s working and why lets us compound performance over time.
Consumption is fragmented and reaching people is harder than ever, despite all of the various touchpoints we have now. People bounce between open and closed ecosystems. AI helps in two ways:
The first is data analysis. The ad tech industry has led the way by finding applications for machine learning, such as ingesting large sets of signals, finding trends, and optimizing towards many sets of variables.
The second is next-gen contextual, which means moving past standard taxonomies into more granular, AI-powered contextual targeting. We’re also evolving our CTV contextual capabilities. Today we can scan show content and align relevant ads to the next break. Next, we’ll layer AI further to improve identification, which is especially useful for live sports where anything can appear on screen, like a type of sneaker on an announcer. And we’re doing the reverse too: scan the ad creative for themes (e.g., Coca-Cola + holidays + togetherness), then place it contextually across inventory where those themes exist.
The web needs quality content and journalism. Kargo supports that with our publisher partners. We’re seeing large publishers strike licensing deals with AI platforms; the open question is what happens to smaller publishers who can’t. We have to avoid a future where only a handful of giants capture all the value. On the buy side, some advertisers are pulling away from display entirely, but we think that has downsides. People still visit publisher pages. As an ecosystem, we should support quality journalism and real information by continuing to invest ad dollars accordingly.
Curiosity and continual upskilling. We’re actively building a conversational media-buying interface. Think talking to a platform like ChatGPT instead of the traditional workflow. Maybe that becomes standard, maybe something else does. The point is to: learn how to prompt, how to leverage AI, and how to bring strategic value through competitive intel, category context, creative insight.
Keep humans in the loop. Our clients want that, and research backs it up. Human-in-the-loop systems consistently perform better. Let AI accelerate, suggest, and optimize; let experts supervise, steer, and explain. That’s our philosophy.
Separating real capability from the “AI” label. We test ruthlessly. For our new contextual solution, we A/B against the prior method on the same campaigns against URL quality, brand safety, CTR, viewability, outcomes, and iterate until there’s a material performance impact. Results first, then launch.
Time savings and efficiency. Tasks that used to take days like trafficking 300 lines, uploading creatives, reconciling tags can compress down to minutes. AI can propose optimizations and draft reporting; humans validate and decide. The win is time back for higher-value work such as creative thinking, client strategy, the next big idea… maybe even a nap.
