The rise of large language models (LLMs) is reshaping how brands are discovered, evaluated and purchased, requiring marketers to adapt their strategies for an AI.mediated environment. This paper introduces generative engine marketing (GEM), a systematic framework for ensuring brands are accurately understood and effectively surfaced by AI systems acting as gatekeepers, audiences and buyers. Using the Share of Model platform, the paper analyses how LLMs perceive brands, construct category narratives and determine visibility through new metrics such as mention rate, average position and category associations. Case studies demonstrate meaningful performance gains when LLM.derived insights are applied to media activation and content optimisation. The paper concludes that brands must strategically shape their machine.readable presence to succeed in the emerging ambient era of marketing. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Smyth et al. (2025) studied this question.