Google is incorporating display advertising into its AI-powered Demand Gen platform, ending the long-standing digital advertising model.
The Google Display Network (GDN) has been a staple of the open internet for almost two decades. Marketers have traditionally relied on its predictive framework to target placements, bid on audiences, and A/B test static creative across news sites and blogs. This familiar setup is changing, and marketing teams need to move away from manual campaign management and rely on Google’s AI.
Google describes this change as a natural progression and presents it as a way for advertisers to access visual platforms like YouTube, Discover, and Gmail through one unified campaign.
Traditional banner ads are facing increasing competition from full-screen video formats on platforms like TikTok and Instagram. In response, Google’s Demand Gen uses automated systems to generate and develop customer interest before a search query is entered.
Demand Gen functionality differs from traditional GDN. Instead of advertisers choosing specific websites or tailoring audience segments, the platform requires a business objective and a collection of creative assets. Marketers upload images, video clips, and headlines, and Google’s AI tests them in different combinations. The system uses predictive models to make format, placement, and audience decisions and delivers them as in-stream video ads, YouTube Shorts, or interactive Discover posts.
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 delivering raw assets that Google’s AI dynamically assembles, moving traditional agency workflows towards higher-volume content creation.
Transaction granularity for automation
Google is betting that machine learning will overwhelm human intuition at scale, effectively forcing industry’s hand. Integrating displays into this AI-centric model removes the temptation for teams to cling to manual methods. Advertisers must adopt an AI-first approach. Otherwise, you risk losing visibility of your valuable digital real estate.
Metrics that have been used for many years, such as click-through rate (CTR) and cost-per-click (CPC), are now losing much of their meaning. When AI optimizes conversions and brand lift across multiple formats and platforms simultaneously, it becomes nearly impossible to determine the success of a single creative or placement. Instead, they need improved reporting capabilities to track broader business outcomes, such as customer acquisition costs, return on ad spend, and impact on the overall buying process.
This requires tighter integration between advertising platforms and companies’ core business intelligence systems. Without accurate, real-time transformation data, AI will fly blind.
For many companies, this dependency exposes critical weaknesses in their data infrastructure. Multi-million pound Demand Gen budgets can hinge on the quality of a single API connection to a CRM or eCommerce backend, which is often built for entirely different purposes.
Meta is driving a similar agenda with its Advantage+ campaigns, leveraging AI to automate targeting, creative, and placement across its ecosystem. The industry is clearly moving from a model of renting advertising space to one of hiring AI agents to hunt down customers.
Marketing leaders no longer have the option of ceding control to AI. The focus is on how to adapt teams, technology, and strategy.
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