IAS’s Srishti Gupta: Media Quality has Shifted ‘From Protection to Growth’
CANNES, France — As AI-generated content floods digital environments, the case for media quality investment has fundamentally changed — moving from defensive brand protection toward measurable performance improvement that drives sales lift, brand awareness, and working media efficiency.
“Media quality has fundamentally changed from being about protection to really being about growth,” Srishti Gupta, chief product officer at Integral Ad Science, told Beet.TV contributor David Kaplan at Cannes Lions. “When consumers see an ad in the right environment, they actually engage with it, they lean in, and that leads to higher outcomes.”
With more than 50% of content now estimated to be AI-generated, brands face unprecedented pressure to ensure their advertising appears alongside appropriate content — creating both challenge and opportunity for media quality technology.
Performance data makes the case
Higher quality media environments generate significant performance improvements, with IAS data showing 35% increases in working media effectiveness, 40% sales lift for consumer packaged goods clients optimizing toward attention metrics, and 30% brand awareness gains for automotive advertisers targeting viewability.
“Just as an example, recently we saw with a CPG client that when they optimized towards higher attention media, they actually saw a 40% increase in sales lift,” Gupta said.
Pre-bid signal integration creates flywheel effects where quality improvements continuously reinforce campaign performance across subsequent media investments.
AI classification operates at unprecedented scale
IAS processes 140 years’ worth of video content daily through multimedia classification models that analyze sentiment, emotion, and cross-language nuance within user-generated and social environments.
“We are able to really build multimedia classification models at tremendous AI scale,” Gupta said. “Our models are not only able to classify it at scale, but then we are also able to go and be extremely nuanced. We can look at sentiment. We can look at emotion. We can look at nuances between languages.”
Fifteen years of model training data enables custom brand-specific classification that tailors quality parameters to individual advertiser requirements rather than generic industry standards.
Total TV bridges buy-sell transparency gap
IAS’s Total TV initiative addresses historical disconnects between publisher and advertiser quality definitions by creating shared visibility layers that align buy-side and sell-side standards across streaming environments.
“We have not only the buy side leaning in, but we also have the sell side leaning in. We have several publishers, for example, Disney and NBCU and Amazon Prime leaning in and sharing signals with us so that brands can be confident on what genres and what programs their ad dollars are appearing against,” Gupta said.
Quality Connect extends this transparency approach by giving publishers visibility into specific brand safety and suitability preferences that were previously invisible to the sell side.
“Brands have very specific preferences around brand safety and suitability, but publishers usually do not have visibility into that. That is where Quality Connect comes in to provide that visibility to both sides so that both sides win,” Gupta said.
You’re watching Beet.TV coverage from Cannes Lions 2026. For more videos from this series, please visit this page.
CANNES, France — As AI-generated content floods digital environments, the case for media quality investment has fundamentally changed — moving from defensive brand protection toward measurable performance improvement that drives sales lift, brand awareness, and working media efficiency.
“Media quality has fundamentally changed from being about protection to really being about growth,” Srishti Gupta, chief product officer at Integral Ad Science, told Beet.TV contributor David Kaplan at Cannes Lions. “When consumers see an ad in the right environment, they actually engage with it, they lean in, and that leads to higher outcomes.”
With more than 50% of content now estimated to be AI-generated, brands face unprecedented pressure to ensure their advertising appears alongside appropriate content — creating both challenge and opportunity for media quality technology.
Performance data makes the case
Higher quality media environments generate significant performance improvements, with IAS data showing 35% increases in working media effectiveness, 40% sales lift for consumer packaged goods clients optimizing toward attention metrics, and 30% brand awareness gains for automotive advertisers targeting viewability.
“Just as an example, recently we saw with a CPG client that when they optimized towards higher attention media, they actually saw a 40% increase in sales lift,” Gupta said.
Pre-bid signal integration creates flywheel effects where quality improvements continuously reinforce campaign performance across subsequent media investments.
AI classification operates at unprecedented scale
IAS processes 140 years’ worth of video content daily through multimedia classification models that analyze sentiment, emotion, and cross-language nuance within user-generated and social environments.
“We are able to really build multimedia classification models at tremendous AI scale,” Gupta said. “Our models are not only able to classify it at scale, but then we are also able to go and be extremely nuanced. We can look at sentiment. We can look at emotion. We can look at nuances between languages.”
Fifteen years of model training data enables custom brand-specific classification that tailors quality parameters to individual advertiser requirements rather than generic industry standards.
Total TV bridges buy-sell transparency gap
IAS’s Total TV initiative addresses historical disconnects between publisher and advertiser quality definitions by creating shared visibility layers that align buy-side and sell-side standards across streaming environments.
“We have not only the buy side leaning in, but we also have the sell side leaning in. We have several publishers, for example, Disney and NBCU and Amazon Prime leaning in and sharing signals with us so that brands can be confident on what genres and what programs their ad dollars are appearing against,” Gupta said.
Quality Connect extends this transparency approach by giving publishers visibility into specific brand safety and suitability preferences that were previously invisible to the sell side.
“Brands have very specific preferences around brand safety and suitability, but publishers usually do not have visibility into that. That is where Quality Connect comes in to provide that visibility to both sides so that both sides win,” Gupta said.
You’re watching Beet.TV coverage from Cannes Lions 2026. For more videos from this series, please visit this page.
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