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Google is folding Display Ads into its AI-powered Demand Gen platform, marking the end of a long-standing digital advertising model.
The Google Display Network (GDN) has been a staple of the open internet for almost twenty years. Marketers previously relied on its predictable framework to target placements, bid on audiences, and A/B test static creative across news sites and blogs. That familiar setup is changing and requires marketing teams to move away from manual campaign controls and rely on Google’s AI.
Google describes this change as a natural progression and presents it as a method for advertisers to reach visual platforms like YouTube, Discover, and Gmail through one consolidated campaign.
Traditional banner ads are facing increased competition from the full-screen video formats of platforms like TikTok and Instagram. In response, Google’s Demand Gen uses an automated system to generate and develop customer interest before a search query is ever entered.
Demand Gen functions differently from the traditional GDN. Instead of having advertisers select specific websites or adjust audience segments, the platform requires business goals and a collection of creative assets. Marketers upload images, video clips, and headlines, which Google’s AI then tests in various combinations. The system serves these as in-stream video ads, YouTube Shorts, or interactive Discover posts, using predictive models to determine format, placement, and audience.
This transition requires changes to creative production. Demand Gen relies on a continuous supply of diverse, format-agnostic content. Creative teams are now tasked with providing the raw assets that Google’s AI assembles dynamically, shifting the traditional agency workflow toward higher-volume content creation.
Trading granularity for automation
Google is betting that machine learning will beat human intuition at scale, effectively forcing the industry’s hand. Consolidating Display into this AI-centric model removes the temptation for teams to cling to manual methods. Advertisers must adopt the AI-first approach or risk losing visibility on valuable digital real estate.