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"Developing a Custom AI Model for Branding: Gartner's Proposal"

Many marketing organizations are using solutions with artificial intelligence (AI) baked in, and many are testing use cases for readily available generative AI. Andrew Frank, VP distinguished analyst at Gartner, suggests a modest proposal: Develop a custom AI model for your brand, beginning with the use case of branding itself. This custom part of the proposal is key. Marketing must move away from “out-of-the-box” solutions, Frank says, and Gartner research shows that, while many consider AI for every use case, marketing is seventh on the list of business functions seen as benefitting from AI. Frank argues that branding is an “fuzzy, abstract” concept, and that generative AI like Chat GPT is well-suited to this, as it can create broadly relevant and more-or-less accurate output, sacrificing precision for relevance. He encourages brands to deploy a foundational AI model, then customize it by training it on the brand's own data. Human oversight and feedback is key to ensure brand values are represented. The project will require input from both marketers and IT and data scientists, with a Model Owner at the heart of the team. This person will not be a hands-on data or AI expert, but will be able to interact with experts and ensure the operational challenges of the project are aligned with the needs of the marketers. Generative AI will create paid media, content and social ads, sites, apps, videos and chatbots, all within the parameters of the brand it has come to understand. Frank is bold enough to suggest that custom training of AI by brands will be mainstream by 2026. It’s easy to see how this could go off the rails without close human attention, and while it’s primarily an enterprise project, it could be achievable with the right team in place.

Originally reported by Martech:
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