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In ad tech, false dichotomies are everywhere. One of the most common is the idea that publishers must choose between human expertise and AI automation when it comes to how they let advertisers buy their inventory. In reality, effective revenue optimization is about knowing when to lean on machine learning and when to trust human judgment.

To understand the decision-making framework that's revolutionizing how publishers approach ad monetization, we spoke with Jayson Dubin, CEO at Playwire. Here are the critical areas where the human vs. AI choice dramatically impacts revenue.

Jayson Dubin: AI is absolutely a revolution, and publishers should treat it that way. But that doesn’t mean the answer is as simple as “automate everything.” AI has extraordinary strengths in certain areas, but human judgment is still indispensable in others.

It’s also important to remember the pressure publishers are under right now. Their businesses rely on audience trust, and that trust has to be respected as they integrate AI tools into operations. Publishers can’t simply hand the keys over to machines without understanding the consequences for their brand, their user experience, and ultimately, their long-term revenue health.

OK, then. Let’s get specific: Where does AI win right now?

Two areas stand out: bid shaping and price flooring.

Bid shaping is the process of filtering and adjusting bid requests in the programmatic auction to ensure that only the most relevant, competitive bids are sent through. Done manually, this is inefficient and leaves money on the table. Algorithms, however, can recognize patterns across geography, device, and supply paths that no human could reasonably track, and they can optimize in real time.

Price flooring is another example. A price floor sets the lowest CPM a publisher is willing to accept for an impression. Traditionally, publishers managed these manually with broad rules, but that approach is outdated. AI can dynamically manage thousands (even millions) of floors simultaneously, adjusting for factors like geography and ad slot performance to maximize yield without constant human oversight.

So what about human intervention? Are there any areas where human judgment still reigns supreme?

Absolutely. One of the most important is with regard to quality and performance initiatives in which publishers decide to prioritize quality over sheer quantity of impressions.

For example, we worked with a publisher who made a conscious decision to reduce overall ad density in order to elevate the user experience. That wasn’t an algorithmic choice; it was a business decision based on an understanding of their audience. The result? Higher CPMs, better engagement, and ultimately a stronger revenue outcome. AI can’t replace that kind of strategic vision. It can only execute once the humans set the course.

That still leaves a lot of publisher decision-making in the gray area between AI and humans. How should publishers think about finding their optimal balance?

The truth is there’s no one-size-fits-all answer. A small publisher with a lean team will need a very different mix of automation and control than a large publisher with in-house programmatic experts.

At Playwire, our approach is to help publishers define their optimal control points. Where does human expertise provide unique value? Where is the workload better handled by automation? From there, we provide to tools needed to go down both paths:

The goal is to give publishers flexibility: control where they want it, automation where they need it.

You mentioned bid shaping earlier. Can you explain why AI is such a game-changer there?

Bid shaping is a perfect case study of why AI matters. Traditionally, publishers would apply broad filters to incoming bid requests, maybe blocking certain geographies or setting static thresholds. But those manual rules are blunt instruments.

When we applied machine learning to bid shaping, we saw a 12% revenue lift for publishers while actually reducing bid requests by 17%. That means publishers made more money with less infrastructure strain, less data processing, and still delivered better performance for buyers. That’s more than just incremental improvement. It’s transformative.

Every good conversation ends with real-life proof. What does Playwire’s human-AI balancing act look like in the wild?

One of my favorite examples is a large education publisher we worked with. They wanted to maintain a positive learning environment, which meant limiting the number of ads shown to students and teachers. That was a human-led strategic decision based on their mission.

Once that choice was made, our AI tools kicked in to maximize revenue within those constraints. Our tools optimized bid shaping, set dynamic price floors, and handled the complexity of programmatic demand at scale.

The result? A 168% increase in CPMs and 76% overall revenue growth. That’s the power of combining human judgment with machine efficiency: Humans define the “why.” AI optimizes the “how.”

About Playwire

Playwire is dedicated to helping publishers, portfolio managers, and app developers accelerate their business by amplifying ad revenue and operating more efficiently. This purpose drives every decision we make; it’s at the heart of every new tool we roll out.

For more information, visit www.playwire.com.

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