AI Can Unlock Streaming’s Untapped Advertising Goldmine: Coactive’s Cody Coleman
Streaming services used to try persuading consumers to pay for the privilege of watching television without commercials. Now they’re discovering that the real money might come from showing those commercials after all.
The rapid growth of ad-supported streaming is transforming the economics of premium video, creating enormous opportunities for advertisers. There’s just one problem: Much of the available programming remains practically invisible to the brands that might want to advertise alongside it.
That’s where artificial intelligence comes in, according to Cody Coleman, co-founder and chief executive of Coactive, who spoke with David Kaplan, a contributor to Beet.TV, at the Beet.TV Leadership Summit with Omnicom Media during Advertising Week New York 2026.
Coleman explained how AI could help advertisers identify valuable moments within streaming programs, improve campaign targeting and extract more revenue from content that’s currently overlooked.
Streaming’s advertising reversal
Ad-supported subscriptions now account for nearly half of all premium streaming subscriptions, Coleman said. About 70% of net new subscribers in recent years have chosen advertising-supported plans, while growth in ad-free subscriptions has stagnated or declined.
Disney+, for example, has seen its ad-supported share climb from single digits to more than 40%. At Peacock, more than 80% of subscribers use an ad-supported plan, according to Coleman.
“So really, the business of streaming is less about subscribers and more about advertisers,” Coleman said.
“It’s really flipped the model where it’s an ad business with a subscriber component.”
For streaming companies that once treated advertising as an unfortunate relic of traditional television, the reversal is striking. Apparently, the future of television looks suspiciously like its past, except with more sophisticated technology and a monthly subscription bill.
The shift also changes the priorities of publishers. Rather than concentrating primarily on attracting subscribers, streaming services increasingly need to maximize the advertising value of audiences they’ve already assembled.
A content goldmine nobody can find
Despite the abundance of premium video, advertisers face growing difficulty identifying programming that matches their campaign objectives.
“Honestly, it’s getting harder,” Coleman said when Kaplan asked whether the explosion of streaming content had made finding suitable advertising opportunities easier.
The problem isn’t a shortage of content. It’s the industry’s inability to describe that content in ways advertisers find useful.
Brands think about emotions, moods and narratives that complement their marketing messages. Publishers, meanwhile, traditionally organize their inventory around programs, channels and dayparts.
That disconnect makes it difficult to match an advertiser’s objectives with relevant scenes buried inside thousands of hours of programming. Coleman estimated that 80% of available content goes untapped because advertisers lack the tools to understand what’s actually happening on screen.
In other words, the industry has assembled an enormous library of potentially valuable advertising opportunities, then apparently misplaced the catalog. The consequences extend beyond inefficient media buying. Publishers may be leaving substantial advertising revenue unrealized, while brands miss opportunities to connect with consumers during moments that reinforce their messages.
AI can find the right moment
Artificial intelligence offers a way to bridge the gap between how advertisers describe their objectives and how publishers categorize their inventory.
“So on the planning side, AI finally gives us the ability to understand the content like humans do,” Coleman said.
Instead of relying on broad program descriptions, AI can analyze what’s happening within individual scenes, including visual elements, emotional tone and narrative context. Work that previously required weeks of manual analysis can now be completed in minutes, Coleman said.
That capability could fundamentally change media planning. Rather than buying inventory based primarily on a program’s genre or audience demographics, advertisers could identify specific moments that complement their brands. A travel company, for example, might seek scenes that evoke adventure or discovery. An automaker could favor moments emphasizing independence or excitement.
The opportunity isn’t simply to find more places to advertise. It’s to find better places within programming that advertisers might otherwise overlook.
Beyond reach and completion rates
AI could also change how marketers evaluate campaign performance. Traditional video advertising measurement has emphasized audience reach and whether viewers watched commercials through completion. Those metrics provide useful information, but they don’t necessarily explain why an advertisement succeeds.
“Now we can actually understand the surrounding context of that ad,” Coleman said.
Analyzing the content surrounding an advertisement could help marketers determine why a campaign performs better in one environment than another.
That adds another dimension to targeting. Instead of focusing exclusively on reaching the right consumer, advertisers could determine when that consumer is most receptive to a particular message. The distinction matters because even the most precisely targeted advertisement can fall flat if it appears at an inappropriate moment.
For marketers accustomed to optimizing campaigns around demographic characteristics and viewing behavior, contextual intelligence could offer a more nuanced understanding of advertising effectiveness.
Stop treating context like a security guard
Coleman’s advice to publishers and advertisers is to rethink contextual targeting, which has frequently been treated as a tool for avoiding unsuitable content rather than finding valuable opportunities.
“They need to stop thinking of context and contextual as a defensive play,” he said.
Brand safety remains important, but filtering programming through broad categories can exclude entire shows or scenes that might actually be appropriate for an advertiser.
A program containing violence, for example, could also feature moments of humor, family connection or celebration that have little in common with its overall classification.
AI-powered analysis could help brands distinguish between those moments rather than rejecting the entire program.
The result could be more available inventory for publishers and more relevant placements for advertisers.
Coleman argued that contextual intelligence should become a core component of advertising strategy, working alongside audience data rather than serving merely as a backup targeting signal.
“What they need to start doing is think about context as a yield story and as a way to do better targeting,” he said.
For publishers, that means potentially generating more revenue from programming they already own or distribute. For advertisers, it means finding opportunities that conventional targeting systems might miss.
And for an industry that’s spent billions of dollars creating, acquiring and distributing video content, the next competitive advantage might not require producing another hit show. It might simply require figuring out what’s already on the screen.
You’re watching “The Beet.TV Leadership Summit with Omnicom Media at Advertising Week 2026,” presented by Cuebiq, Databricks, Newton Research, Roku and Teads. For more videos from this summit, please visit this page.
Streaming services used to try persuading consumers to pay for the privilege of watching television without commercials. Now they’re discovering that the real money might come from showing those commercials after all.
The rapid growth of ad-supported streaming is transforming the economics of premium video, creating enormous opportunities for advertisers. There’s just one problem: Much of the available programming remains practically invisible to the brands that might want to advertise alongside it.
That’s where artificial intelligence comes in, according to Cody Coleman, co-founder and chief executive of Coactive, who spoke with David Kaplan, a contributor to Beet.TV, at the Beet.TV Leadership Summit with Omnicom Media during Advertising Week New York 2026.
Coleman explained how AI could help advertisers identify valuable moments within streaming programs, improve campaign targeting and extract more revenue from content that’s currently overlooked.
Streaming’s advertising reversal
Ad-supported subscriptions now account for nearly half of all premium streaming subscriptions, Coleman said. About 70% of net new subscribers in recent years have chosen advertising-supported plans, while growth in ad-free subscriptions has stagnated or declined.
Disney+, for example, has seen its ad-supported share climb from single digits to more than 40%. At Peacock, more than 80% of subscribers use an ad-supported plan, according to Coleman.
“So really, the business of streaming is less about subscribers and more about advertisers,” Coleman said.
“It’s really flipped the model where it’s an ad business with a subscriber component.”
For streaming companies that once treated advertising as an unfortunate relic of traditional television, the reversal is striking. Apparently, the future of television looks suspiciously like its past, except with more sophisticated technology and a monthly subscription bill.
The shift also changes the priorities of publishers. Rather than concentrating primarily on attracting subscribers, streaming services increasingly need to maximize the advertising value of audiences they’ve already assembled.
A content goldmine nobody can find
Despite the abundance of premium video, advertisers face growing difficulty identifying programming that matches their campaign objectives.
“Honestly, it’s getting harder,” Coleman said when Kaplan asked whether the explosion of streaming content had made finding suitable advertising opportunities easier.
The problem isn’t a shortage of content. It’s the industry’s inability to describe that content in ways advertisers find useful.
Brands think about emotions, moods and narratives that complement their marketing messages. Publishers, meanwhile, traditionally organize their inventory around programs, channels and dayparts.
That disconnect makes it difficult to match an advertiser’s objectives with relevant scenes buried inside thousands of hours of programming. Coleman estimated that 80% of available content goes untapped because advertisers lack the tools to understand what’s actually happening on screen.
In other words, the industry has assembled an enormous library of potentially valuable advertising opportunities, then apparently misplaced the catalog. The consequences extend beyond inefficient media buying. Publishers may be leaving substantial advertising revenue unrealized, while brands miss opportunities to connect with consumers during moments that reinforce their messages.
AI can find the right moment
Artificial intelligence offers a way to bridge the gap between how advertisers describe their objectives and how publishers categorize their inventory.
“So on the planning side, AI finally gives us the ability to understand the content like humans do,” Coleman said.
Instead of relying on broad program descriptions, AI can analyze what’s happening within individual scenes, including visual elements, emotional tone and narrative context. Work that previously required weeks of manual analysis can now be completed in minutes, Coleman said.
That capability could fundamentally change media planning. Rather than buying inventory based primarily on a program’s genre or audience demographics, advertisers could identify specific moments that complement their brands. A travel company, for example, might seek scenes that evoke adventure or discovery. An automaker could favor moments emphasizing independence or excitement.
The opportunity isn’t simply to find more places to advertise. It’s to find better places within programming that advertisers might otherwise overlook.
Beyond reach and completion rates
AI could also change how marketers evaluate campaign performance. Traditional video advertising measurement has emphasized audience reach and whether viewers watched commercials through completion. Those metrics provide useful information, but they don’t necessarily explain why an advertisement succeeds.
“Now we can actually understand the surrounding context of that ad,” Coleman said.
Analyzing the content surrounding an advertisement could help marketers determine why a campaign performs better in one environment than another.
That adds another dimension to targeting. Instead of focusing exclusively on reaching the right consumer, advertisers could determine when that consumer is most receptive to a particular message. The distinction matters because even the most precisely targeted advertisement can fall flat if it appears at an inappropriate moment.
For marketers accustomed to optimizing campaigns around demographic characteristics and viewing behavior, contextual intelligence could offer a more nuanced understanding of advertising effectiveness.
Stop treating context like a security guard
Coleman’s advice to publishers and advertisers is to rethink contextual targeting, which has frequently been treated as a tool for avoiding unsuitable content rather than finding valuable opportunities.
“They need to stop thinking of context and contextual as a defensive play,” he said.
Brand safety remains important, but filtering programming through broad categories can exclude entire shows or scenes that might actually be appropriate for an advertiser.
A program containing violence, for example, could also feature moments of humor, family connection or celebration that have little in common with its overall classification.
AI-powered analysis could help brands distinguish between those moments rather than rejecting the entire program.
The result could be more available inventory for publishers and more relevant placements for advertisers.
Coleman argued that contextual intelligence should become a core component of advertising strategy, working alongside audience data rather than serving merely as a backup targeting signal.
“What they need to start doing is think about context as a yield story and as a way to do better targeting,” he said.
For publishers, that means potentially generating more revenue from programming they already own or distribute. For advertisers, it means finding opportunities that conventional targeting systems might miss.
And for an industry that’s spent billions of dollars creating, acquiring and distributing video content, the next competitive advantage might not require producing another hit show. It might simply require figuring out what’s already on the screen.
You’re watching “The Beet.TV Leadership Summit with Omnicom Media at Advertising Week 2026,” presented by Cuebiq, Databricks, Newton Research, Roku and Teads. For more videos from this summit, please visit this page.
