Brands are already finding creative uses for agentic AI across their business, from Burberry deploying agents to spot counterfeit products to Ralph Lauren's virtual shopping assistant, Ask Ralph. Agentic AI is poised to transform every stage of advertising – influencing how campaigns are developed, managed, delivered and measured.
After nearly two decades in the programmatic ecosystem, brands have heard words like "scale," "automation" and "control" more times than they can count (not to mention "efficiency"). Agentic AI works differently and can perform entirely new functions that improve the current programmatic supply chain and deliver on these promises. Agentic AI not only automates processes, but it can also learn and act autonomously, making decisions in real time.
Here are the five agentic AI capabilities that go above and beyond programmatic I am most excited about in 2026:
The creative process will benefit from agentic AI in several ways. Agents can be deployed to work with creative teams at the beginning of the design process, cultivating an understanding of the brand's creative look and feel. They can also be used to review ads in the wild to make sure they are brand and platform compliant and reformat and resize ads in a fraction of the time of manual work, providing a lot more creative variation. Brands that use agentic AI in their creative process will dramatically reduce the time it takes to develop creative designs and have a much bigger set of creative assets that will be high-quality and performant.
Creative also benefits from AI when it comes to insights and optimization. AI gives advertisers access to creative intelligence that can drive meaningful campaign improvements. Quality creative is the largest contributor to campaign outcomes, according to Kantar; however, until AI, digital advertising technology wasn't equipped to evaluate individual campaign elements to give advertisers granular insights for specific creatives, campaigns or benchmark insights. With AI, advertisers can understand what aspects of a creative design matter most. Dynamic creative optimization can become supercharged with AI insights.
Media teams spend long hours manually uploading information into platforms at every stage of the campaign process. Agentic AI can automate this process and save brands and agencies thousands of hours of manual work every week. Agents can be trained to manage campaigns across platforms, eliminating repetitive work and reducing errors, with media buyers at the helm, guiding AI tools to ensure they remain effective and accurate.
Media operations, trading and other teams can start to focus on more interesting work like optimization and analytics rather than being stuck handling data entry for hours on end. Having AI as a tool that reduces manual work and speeds up the campaign management process can dramatically improve the velocity and quality output of the (human) media team.
Programmatic advertising relies on data, but agentic AI leverages far more, and uses it to drive deeper insights and actions. Agents can access a huge range of data sets and perform sophisticated campaign measurement and optimization that used to be manual and expensive. There are agentic AI solutions available today that can do MMM and incremental lift easily, quickly and at a much lower cost.
Agentic AI can also dramatically increase the scope of information available to brands during the media buying process, so that they can find very specific audiences and use nuanced content data.
Brands can use agents to manage media buying strategies across partners and platforms. Any brand that works with multiple DSPs, walled gardens and media companies knows how difficult it can be to get a complete picture of campaign spend, optimization and audience coverage.
Agents can pull together information from across partners to bring these disparate parts of a media plan together. This can help solve many thorny programmatic problems from frequency capping to normalizing bids and reducing redundancies.
So much changes when a media buyer can simply type a request into a chatbot rather than build a complex campaign on a spreadsheet and then manually enter the information into a platform UI. Everyone on the team is freed from the heavy lifting that goes along with any campaign change or improvement, with the ability to make more changes and more improvements.
Brands naturally benefit when improving campaigns becomes intuitive and easy. Imagine how many more tests a media team can run when they can simply tell an agent how to set it up and what to measure. Consider the number of different innovations a campaign can incorporate when each one doesn't add hours to the setup process.
A new report from MIT and BCG finds that agentic AI "blurs the line between tool and teammate" with 76 percent of executives viewing agentic AI as more of a coworker than a technology. With that description, the difference between programmatic tech and agentic AI becomes clear. No one would say that a DSP is just like a coworker.
Programmatic automates the core elements of buying media like bidding on impressions, targeting audiences and automating auctions. It's a rules-based technology that can transact at very high volumes but can't do anything autonomously. There is a lot of manual work that supports programmatic.
AI agents are lightweight specialists, performing automations that fit a very specific advertiser need. And the good news is that they are easy to adopt and use. In 2026, Agentic AI won't just eliminate barriers, it will accelerate growth.