Adobe Advertising pitches practical AI framework for marketers

By AI, Created 4:34 PM UTC, May 18, 2026, /AGP/ – Adobe Advertising published a CMO Alliance article from Head of Product Greg Collison outlining how marketers can use predictive, generative and agentic AI together. The piece argues that better performance depends on matching the right AI capability to bidding, creative work and workflow automation, not chasing automation alone.

Why it matters: - Adobe Advertising is trying to shape how marketers think about AI at a time when ad platforms are adding more automation and AI features. - The framework matters because Collison argues that performance gains depend on combining AI types, not treating AI as a single tool. - Marketers that use the wrong AI layer for the job risk adding complexity without improving return on media investment.

What happened: - Adobe Advertising announced the publication of a new CMO Alliance article by Greg Collison, Head of Product, Adobe Advertising. - The article, titled “A Framework for Practical AI in Advertising,” focuses on how AI is changing advertising platforms. - The piece is available now on CMO Alliance.

The details: - Collison divides AI in advertising into three categories. - Predictive AI underpins performance by analyzing signals and optimizing bidding. - Generative AI expands creative options by enabling faster asset creation and variation. - Agentic AI simplifies workflows by helping marketers set up campaigns, interpret results and automate routine tasks. - Collison says AI is becoming central to how marketers plan, activate and optimize campaigns. - He argues the industry needs a clearer framework for understanding what each AI capability does. - The article says advertisers should evaluate how the three categories work together to improve business outcomes. - Collison says practical value comes from combining predictive, generative and agentic AI to reduce complexity, improve creative experimentation and drive stronger outcomes. - The article says agentic AI is likely to be one of the most visible areas of innovation in advertising platforms. - Workflow automation alone does not guarantee stronger performance, according to the article. - Collison says marketers should first assess the strength of a platform’s predictive systems and data foundation. - The article says automation can only optimize within the limits of the underlying performance engine. - The byline encourages marketers to ask whether advertising partners are using organic site traffic to train predictive models. - It also asks whether partners are testing multiple DSPs to understand performance differences. - The article recommends experimenting with generative AI to create more ad variants. - It also points marketers toward partners developing agentic experiences to reduce manual work. - Collison concludes that practical AI in advertising is about using AI across performance, creative and workflow automation. - He says the goal is to eliminate busy work while maximizing return on media investment.

Between the lines: - Adobe Advertising is positioning itself on the side of measured AI adoption, with an emphasis on foundations like data quality and predictive performance. - The article also reads as a warning that visible AI features can distract marketers from the systems that actually determine results. - The emphasis on practical questions suggests Adobe Advertising wants buyers to scrutinize vendor claims more closely.

What’s next: - Marketers are likely to use the framework as a checklist when evaluating adtech partners and AI-enabled platform features. - Adobe Advertising is likely to continue promoting AI tools that connect performance optimization, creative generation and workflow automation. - The article sets up a broader conversation around how advertisers should measure AI value beyond efficiency alone.