AI Mythbusters #2: (Still) debunking the biggest AI misconceptions in advertising
In last month’s blog, we dove into three emerging misconceptions for AI in advertising, mostly centered around uncertainty for the future—robots taking jobs, data replacing strategy, and the risk of placing too much trust in AI’s opinions.
This time, we’re focusing on the hype surrounding AI’s promised capabilities. With every new AI demo and headline, our industry is flooded with lofty promises of instant transformation and seamless optimization. But beneath the buzz, there are still a few myths worth untangling.
In this second installment of our AI Mythbusters series, we’re diving into three new misconceptions —and why understanding the truth behind them is critical for marketers who want to stay ahead.
Myth #4: AI will create a single automated solution to rule them all
With the constant innovation surrounding AI, it’s easy to imagine one sleek platform that can handle everything in advertising, from creative to targeting to measurement, making the current fragmented ad tech ecosystem obsolete and unnecessary. But that’s not how the industry works, and not how AI scales.
The reality is AI won’t replace the pipes, but it will run through them. Successful AI advertising tools still depend on integrations with the foundational players—ad servers, DSPs, measurement platforms, data providers, and creative management systems—to operate. AI might make these workflows smarter and faster, but it can’t rebuild decades of infrastructure overnight.
That’s why interoperability should be central to AI strategies. It’s about connecting systems. Not necessarily consolidating them.
As Mediaocean CEO Bill Wise put in a recent Wise Words, “When you look at how [AI startups] are going to be successful, you have to ask how they’re going to activate the solutions that they’re building. It’s by integrating into the legacy systems—the incumbents in the space.”
New AI solutions won’t erase the ad tech stack, but strengthen it. The winners in this new era will be the solutions that connect AI capabilities to existing systems to drive interoperability rather than isolation.
The newly-announced AdCP is an example of an industry initiative that shows promise for ensuring connectivity. And stay tuned for big news from Innovid on how we’re addressing the larger opportunity here.
Myth #5: AI success is all about who has the best model
There’s a misconception that AI dominance will be decided by which company builds the most powerful or advanced model. But in advertising, success won’t hinge on having the “smartest” AI, it will depend on data relevance and the best human application.
Large language models may power the underlying intelligence, but their outputs are only as useful as the context and data pipelines they connect to. The smartest model in the world won’t matter if it’s disconnected from the data that actually drive real business results.
That’s why real success comes from applying AI within the right context—connecting it to creative performance, audience behavior, and measurable outcomes.
The edge will go to brands and tech partners who combine first-party insights, creative context, and campaign data to train models that truly understand advertising intent, not just generic patterns in text or images.
In short: it’s not about raw intelligence, it’s about applied intelligence.
Myth #6: AI will make advertising results guaranteed
AI’s promise of automation and optimization leads many to believe that it will make advertising perfectly efficient, where campaigns run themselves and results are guaranteed. But there will always be unpredictable factors. Things like creativity, culture, and consumer behavior don’t follow algorithms.
Yes, AI can forecast trends, predict audience affinities, and automate testing. And with seasonal shifts you know are coming (like cold and flu season), AI can significantly improve planning and execution. That said, advertising still lives in a fluid world where timing is everything—one where moods constantly shift, anything can instantly go viral, and social media operates as a cultural force.
That’s why AI should be seen as a co-pilot, not an autopilot. It helps marketers work faster and smarter, but humans still provide the spark that makes campaigns connect emotionally and culturally. AI doesn’t eliminate uncertainty; it gives marketers the ability to respond to it in real time.
The magic happens not when AI controls the outcome, but when humans use it to amplify intuition with intelligence.
The takeaway: The future lies in evolution, not replacement
Just as in our first installment, the truth remains: AI is here to enhance advertising, not reinvent it from scratch. The path forward isn’t about chasing one-size-fits-all tools or perfect efficiency—it’s about layering AI into the ecosystem that already works and letting it evolve from there.
The future of AI in advertising is about building a smarter, more interoperable ecosystem together.