Brands in the AI Era: Generative Engine Marketing

For decades, brand strategy has been designed primarily for human audiences. But today AI systems are becoming active participants in the customer journey. They interpret content, recommend products and in some cases can even transact on behalf of users. This shift marks the emergence of a new marketing context the authors call the “ambient era”, where brands must be visible and understandable not only to people but also to AI systems.

To address this change, Generative Engine Marketing (GEM) is a strategic framework designed for the AI era. GEM extends traditional brand strategy to account for how AI models perceive, interpret and surface brands across digital environments. Rather than focusing only on human behavior, it encourages marketers to optimize brand signals for both human audiences and AI systems that increasingly act as gatekeepers, advisors and buyers.

The framework highlights several critical shifts. AI now plays multiple roles in the marketing ecosystem: it curates and recommends information, interprets brand content across text, image and video formats, and is rapidly evolving toward autonomous purchasing through agentic commerce. As a result, brands must consider how they appear within AI responses, what sources influence model outputs and how their content is interpreted by machines.

GEM provides a practical system for navigating this environment. It enables marketers to analyze how AI models perceive brands, measure their visibility in model-generated responses and optimize assets, data and media strategies accordingly. New metrics such as “mention rate” and “average position” help brands understand their prominence inside AI systems, while insights about citation sources and category perceptions reveal how models form opinions about brands.

Operationally, GEM integrates technical optimization, content strategy, testing, distribution and measurement into a continuous cycle. When applied effectively, these insights can improve campaign performance and unlock measurable gains in media effectiveness, demonstrating that optimizing for AI systems can directly drive business results.

However, implementing GEM requires organizational change. Because AI touches multiple stages of the marketing process, teams across brand, media, SEO, content and e-commerce must collaborate more closely. Marketers must also evolve their measurement frameworks to account for how AI systems influence discovery, consideration and purchase.

Ultimately, the rise of AI does not replace marketing. Instead, it expands the scope of brand strategy. Success in this new era will belong to brands that design their presence not just for audiences, but for the AI systems that increasingly shape how those audiences discover and choose them.