RANCHO PALOS VERDES, CA — Among advertisers’ hopes for artificial intelligence is the ability to shape and reshape creative moments within scenes streaming on CTV to bring more emotionally resonant ad experiences at scale.
“Every piece of content that we all watch elicits a different emotional reaction or an association. So why shouldn’t the creatives be aligned to that type of content that I’m watching?” Inderpreet Sandhu, global head of CTV Partner Development & Growth at Google Ad Manager, told Beet.TV contributor David Kaplan at the Beet Retreat LA. “If I’m watching an outdoorsy show and I see an ad for a car, it probably should be an outdoorsy type car versus a convertible or a minivan.”
Achieving this contextual creative alignment across diverse advertisers and content at scene-level granularity requires AI to manage complexity that manual processes cannot handle, Sandhu said.
Efficiency drives publisher AI adoption
Publishers seek AI applications that reduce friction in existing processes while providing suggestions for new opportunities, enabling faster campaign execution and iteration with limited resources.
“They have to do a lot with a lot less. They have very few resources now, and they look to us to help them provide not just ways to reduce friction in existing processes, but also to find helpful suggestions,” Sandhu said.
The goal centers on getting campaigns launched quickly while enabling rapid learning to create optimal experiences for consumers and brands.
Data mapping unlocks audience selling
Publishers need efficiency improvements in workflows that don’t remove them from core responsibilities, particularly around enabling first-party audience data offerings through Google’s Publisher Provided Signals framework.
“We have this concept called publisher provided signals, which is a great secure way for publishers to share their first party data with trusted third parties, whether that’s a bidder, an agency, anyone in between,” Sandhu said.
Google’s AI Map feature automates the laborious process of mapping proprietary publisher taxonomies to standardized buyer-understood formats, eliminating manual conversion work.
Regional needs vary
Different markets pursue AI applications based on their specific infrastructure and competitive dynamics, from Latin American publishers bridging traditional over-the-air broadcasting with ATSC 3.0 addressability to European publishers managing consumers across pay TV, FAST, and direct-to-consumer platforms.
“A Latin American publisher is fully leaning in on next generation over the air, ATSC 3.0. They are looking to say, ‘How do I bridge the linear, traditional over-the-air environment with this now new digitally addressable way?’” Sandhu said.
European publishers face different challenges around delivering optimal experiences as individual consumers move between subscription services, FAST channels, and live events throughout their day, requiring tooling that recommends appropriate ad formats from 15-second spots to pause ads or squeeze-backs based on viewing context.
AI embedded in monetization
Effective yield management, ad serving, and monetization already require AI as foundational infrastructure rather than optional enhancement, making the technology invisible to end users.
“You can’t do effective monetization, yield management, or even ad serving without AI already built into it,” Sandhu said. “To do that on the scene level, to do that at scale across a diverse group of advertisers and also content, that’s a lot of complexity. It may not sound good when someone talks about it, but when you see it in action, it’s going to be really impactful.”
