Catch The Next One.
Stay tuned for our next blog focused around how AI impacts account services.
For years, AI and machine learning have quietly enhanced media buying, especially in programmatic environments. What recently brought AI to the forefront for the masses is the development of large language models (LLMs). That shift dropped the curtain, making AI accessible and usable. And this matters.
Not because AI can think like a human. It can’t. But because it excels at recognizing patterns, predicting outcomes, and helping teams move faster with more confidence.
Programmatic Just Got Bigger
Media teams have continued to rely on predictive modeling to optimize bids and audience segments. With sufficient data, systems can predict which combinations are most likely to deliver high-performance results.
What’s changed is the scope. Programmatic buying is no longer limited to display ads. Broadcast TV, radio, out-of-home, and even print (yes, print) are increasingly available through programmatic systems.
At its core, programmatic media buying is computers talking to computers. Inventory comes with parameters. Buyers set theirs. Smarter modeling leads to better matches and better buys. It’s like the stock market where speed and intelligence matter.
LLMs help solve a long-standing challenge: translation. Computers historically required exact inputs, while people are notoriously terrible communicators. LLMs bridge that gap by identifying patterns. They don’t understand language, but they’re excellent at predicting what outcome someone is trying to achieve.
That makes them terrible therapists and very good data analysts.
Platforms Feel the Shift First
AI’s most immediate impact shows up at the platform level. Platforms sit on massive amounts of data, and AI helps organize and activate it in ways that feel intuitive. That’s why algorithms surface content you didn’t explicitly search for but still want. It isn’t magic, just pattern recognition at scale.
For agencies, this means targeting appears simpler on the surface but is more complex beneath the surface. If used correctly, AI is a multiplier. It uncovers unexpected audiences, accelerates optimization, and enables faster decision-making. But it only works when humans define the right outcomes first.
Machines Are Fast, People Are Smart
AI excels at research, analysis, trend identification, and visualization. It’s fast, efficient, and incredibly useful across early and mid-stage media work.
What it can’t reliably do is determine the right strategy. AI doesn’t produce award-winning ideas. It doesn’t understand human motivation or connect cultural signals to meaning. Those are human skills, and they remain irreplaceable.
“AI belongs behind the scenes. It supports critical thinking. It doesn’t replace it. Final strategies, recommendations, and public-facing work should always be shaped, challenged, and validated by people who understand both the data and the humans behind it.”
Advantage or Equalizer? Both.
AI can level the playing field. Smaller teams can move faster, and tasks that once required scale are now accessible with the right tools.
But true advantage comes when high-performing humans use AI well. When experienced strategists offload mechanical work, they gain time to think bigger, push ideas further, and elevate work beyond “good enough.” AI doesn’t make someone exceptional; it amplifies what already exists.
Trust, But Verify
Used carelessly, AI introduces real risks.
Privacy is one. Anything fed into a system can be learned from or shared, so sensitive data must be handled carefully.
Accuracy is another. AI produces answers that sound right, but can’t validate them. Accepting recommendations without scrutiny is a fast way to waste money.
“Media is not cheap, and if you run a million-dollar campaign based solely on what AI said, you may wind up having wasted a million dollars on the wrong audiences and on the wrong placements. Not being critical of AI responses is a big risk.”
AI should inform decisions, not finalize them.
Transparency is Table Stakes
Our clients always deserve transparency. They should know when AI is used, how it’s used, and how human expertise owns the process.
What they should expect is speed, efficiency, and smarter optimization. Used responsibly, AI helps teams move faster, improve targeting, expand reach, and place media with greater precision. It elevates good work.
AI in Action at Stoltz
I believe the AI space will consolidate. Hyped tools will fade, and what remains will be more enterprise-focused, a bit more expensive, and more concerned with safety and data validation.
As AI matures with enterprise-level solutions, media buying will become easier to execute and harder to master. Interfaces will simplify. Technical barriers will fall. The differentiator won’t be access to tools. It will be human expertise.
That’s how we approach AI at Stoltz.
We use AI to get smarter before a campaign ever launches, supporting research, comparison, and early-stage planning. It helps us surface potential placement deals, identify patterns, and dial in options more efficiently. Once live, it supports faster reporting and optimization, allowing us to spot trends sooner. This will be a big game-changer.
I think it’s important to remember that AI doesn’t replace conversation or strategy. The best deals still come from relationships. The strongest recommendations still come from people who apply critical thinking to both the data and its context.
As media buying evolves, execution will continue to accelerate. Thoughtful decision-making won’t. And that’s where human expertise remains essential.
Final Take
AI isn’t a replacement for media buying; it’s an accelerator.
Fast, powerful, and occasionally (very) unpredictable. In the right hands, it scales great work. In the wrong ones, it scales mistakes.
AI won’t replace critical thinking, human insight, or contextual judgment. Those are human strengths, and they’re not going away.
So we’ll keep using AI as a tool, not a crutch, and apply the thinking that makes great media work.
Learn more about Stoltz’ views on AI.
