Brand Strategy

A speech to discover what brand jingles are, their purpose, and why they are significant. Featuring practical examples to construct one's own.

By now, most brands are using AI in some capacity. But few understand how and why these systems make decisions - which means they’re not actually leveraging AI. Joya Scarlata and Mara Dettmann, hosts of The Marketer’s Guide to the AI Galaxy, unpack the gap between AI adoption and real AI literacy in a session which challenges how brand leaders think about measuring AI success and what “capability” really means in the age of agentic systems. They ultimately introduce a more grounded framework for working with AI - because when everyone has access to the same tools, the real competitive edge comes from understanding what those tools are actually doing, and knowing how to steer them.

Generative AI has theoretically revolutionized content creation. In practice, however, brands face a paradox: it has never been easier to produce unlimited volumes of content and it has never been harder to ensure that this content actually looks and feels like the brand. The result is an abundance of generic, interchangeable, visually identity-less assets that rarely deliver on KPIs. In a world where content is the most powerful brand touchpoint, this isn’t just inefficient — it’s risky. This keynote introduces a scientifically developed workflow that bridges the gap between brand identity and AI. It demonstrates how brands can empirically decode their visual DNA, align generative AI with it, and predict performance before anything goes live. Three developments sit at the core and they define the future of content creation: 1. From Generic Output to Brand-Specific Signature How the visual DNA of a brand can be algorithmically captured and why this is the foundation for truly differentiated, recognizable, and on-brand GenAI content. 2. KPI-Optimized Generation Instead of Trial-and-Error How content can be guided not only by aesthetics but by data, enabling more precise targeting, stronger relevance, and higher performance across the entire consumer journey. 3. Predicting Performance Before Content Goes Live How AI reduces human subjectivity in content selection, minimizes creative risk, and enables faster, more confident decision-making. The keynote blends research insights, practical examples, and learnings from data-driven brand communication. It shows how brands will use AI in the coming years not to simply produce more content, but to create better content; content that is on-brand, KPI-effective, and scientifically validated. This is how generative AI evolves from a creative guessing game into a validated system that unifies brand identity, KPIs, and performance prediction into one scalable workflow.

The audience isn’t looking for originality. They want to recognize themselves. They seek the comfort of the familiar, the confirmation of their own ideas. They want to see themselves reflected in words they didn't know they had inside. This is why memes, tropes, jokes, and formats repeat infinitely: virality is simply rewriting what everyone already knows, with a slightly different twist. We defend the idea of originality as a measure of value because we are afraid to admit it’s not true. Admitting that a content’s success stems from skill, context, timing, and a pinch of luck strips the magic away from the myth of the "genius." It’s a less romantic story, but a truer one. If anyone can remix, then anyone can succeed. And that is exactly what scares us. The myth of originality is overrated, but imagination is not. True skill lies in reimagining, recombining, and transforming what already exists into something surprising. Ideas explode when a familiar model is bent at just the right angle. If this bothers you, then ask yourself: “Would I rather defend the illusion of being original, or create something that actually gets people talking?”