This conceptual analysis explores Meta's proposed AI-driven advertising strategy, where algorithms handle everything from creative generation to targeting and optimization, drawing parallels to established quantitative marketing concepts like ad response modeling, consumer heterogeneity, and dynamic optimization. The text discusses how this automated approach aims to maximize advertising outcomes for businesses but also raises concerns regarding advertiser control, strategic learning, and brand consistency. Furthermore, it addresses significant ethical considerations such as algorithmic bias, data privacy, and fairness in ad delivery, and analyzes the potential impact on the advertising ecosystem and the role of marketing analytics professionals.