Logistics is no longer just a back-office function that gets goods from A to B; increasingly, it is where firms win or lose customers, and where operating costs quietly determine whether growth is sustainable. Artificial intelligence (AI) has moved into nearly every corner of this function, from demand forecasting to warehouse robotics to the chatbot that tells a customer their parcel is running late. What is less settled is how these gains actually flow through to two outcomes firms care about most: how the market perceives them, and whether the numbers hold up over time. This paper works through that question by pulling together three streams of theory, the resource-based view, dynamic capabilities theory, and the technology-organization-environment framework, into a single account of how AI-enabled logistics capability shapes marketing performance and financial sustainability, and how those two outcomes feed back into one another. Three objectives guide the paper: examining how far AI adoption in logistics shapes marketing-relevant outcomes such as customer satisfaction, service responsiveness, delivery accuracy, and brand competitiveness; assessing what AI-driven logistics practices do for financial sustainability, including cost efficiency, profitability, resource optimization, and resilience; and asking how marketing performance and financial sustainability relate to each other once AI is added to the picture, whether as a mediator, a moderator, or both. A set of theoretical propositions is developed along the way and illustrated against real, publicly available data comparing two major logistics carriers with markedly different AI-adoption timelines. A concrete design for testing the propositions directly, a matched multi-informant survey analyzed with partial least squares structural equation modeling, is also set out, followed by a discussion of what this means for theory and for practice, and a closing look at the argument's remaining limitations....