An AI advertising platform is software that runs an advertiser's online campaigns with very little human work. The advertiser supplies a goal, a budget and the product. The software then chooses the audience, makes the ads, sets the bids and moves money between campaigns. It is also called an AI marketing platform, or AI campaign automation.
Running ads online used to take a lot of hand work. A marketing team set up separate campaigns on Google, on Meta's apps and on other websites. It chose audiences by age, city and interests. It made dozens of versions of each ad. Then, every few days, it read the reports and moved money from the weak campaigns to the strong ones. An AI advertising platform does these tasks itself, every day or even every hour.
Say a skincare brand that sells online gives the platform a budget of ₹10 lakh for one month. The goal is sales, at no more than ₹400 of ad spending for each order. On the first day, the platform uses generative AI to create 40 versions of the ad from the brand's product photos and descriptions. It spreads the budget across Instagram, YouTube and a demand-side platform (DSP), the software that bids for ad space on other websites and apps. After a week, it finds that each order from Instagram cost ₹320 of ads, but each order from YouTube cost ₹610. So it moves ₹1.5 lakh of the remaining budget from YouTube to Instagram. It also pauses the 25 versions that almost nobody tapped. A person in the brand's marketing team reads a daily report and must approve any larger change.
The difficulty is that each large platform is a walled garden. Google, Meta and Amazon sell ads inside their own apps, with their own tools, and they share only limited data about who saw which ad. So an independent AI platform must work through the connections that each one offers to outside software. The large platforms also offer their own AI campaigns, in which the advertiser supplies only a goal and a product. Independent platforms compete by working across all of them at once.
The advertiser also needs to know whether the ads really caused the sales. The platform can use the estimates of marketing mix modelling (MMM), which works out what each channel added to sales from months of totals. It can also send new ad parts to dynamic creative optimisation (DCO) software, which fits each ad to the viewer.
This is an early example of AI software that spends money for someone, the idea behind agentic commerce. The same question applies to both: what may the software decide alone, and what must a person approve?