Current Uses of AI in CTV and Streaming Ad Ops
How are publishers and advertisers leveraging AI in CTV ad ops in 2026? According to IAB Tech Lab COO and EVP of product Shailley Singh, managing creative and data coming out of campaigns are two key areas; others include prevalidating creative and generating contextual data, says Sargeway, LLC owner Sarge Sargent. Both explain how these processes work and the value AI adds in this discussion with Streaming Media contributing editor Nadine Krefetz from Streaming Media Connect 2026.
AI in Creative and in Data Management
Krefetz addresses Singh to ask what uses of AI in ad ops he spends time thinking about.
Singh points first to creative: “You’ve done your ad, you need to send it to the seller or the publisher for their approval and manage that whole process. So that’s one big area. The other area that I’ve heard is just managing the data and optimization, like what’s coming out of the campaigns, and being able to see that and using an agent to be able to reason over that, and allowing you to have a much more continuous stream of alerts and inferences from the data.”
He notes that traditional software was designed to enable humans to do the work, whereas AI software systems do the work themselves. “So wherever we see laborious human-intensive work, I think that’s where people are looking at opportunities to use AI to create more efficiency and effectiveness in all of those areas,” he believes, pointing to IAB Tech Lab’s creative management API in development, “which will also be extended to a creative management agentic so that between agents and within your own company, you can have a better handle on managing the creative and ensure that it’s ready for serving in the right environments.”
Krefetz asks, “Do they get a unique ad ID for every version of a creative that’s created?”
Singh confirms that IAB Tech Lab has been aiming for that for the past couple of years. “Some of the bigger companies have done that, but it still needs more adoption. And it’s a simple thing, but it solves many complex problems,” he explains.
More Uses of AI in Ad Ops
Krefetz turns to Sargent to inquire, “So in terms of ad operations, where are the other areas that AI has been used?”
“I think Shailley [Singh] touched on a bunch of them as far as campaign management and monitoring yield and delivery,” Sargent says. “We also use it on the playout side. So making sure the ads actually play out and then looking at that data from your beacon standpoint and your validation standpoint. So, IVT details. Rolling all that into an operational view into a dashboard where you, a human, can actually look at it and make sense of the noise in real time.”
He brings up contextualized ads, citing a fellow panelist who spoke earlier about a use case with “an actress who is in the scene but you don’t want her in the ads or vice versa. [Or] you have a player who’s being dominated on the court or on the field, so you want to feature whatever he’s sponsoring. So those are use cases where I’m seeing AI being used. I think that covers the whole gamut from creation through delivery.”
Sargent wants to ensure that they discuss prevalidation. “When you’re ingesting your creatives and going through a QC process and using AI to prevalidate the creative that comes in, whether it just be the right format, whether it be the content in the creative,” he notes, it must be made safe to play on a given platform. It also must be “kick[ed] out before your human views it.”
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