This article discusses the pitfalls and opportunities of AI in marketing through the lenses of knowledge creation and knowledge transfer. First, we discuss the notion of “higher-order learning” that distinguishes AI applications from traditional modeling approaches, and while focusing on recent advances in deep neural networks, we cover its underlying methodologies (multilayer perceptron, convolutional, and recurrent neural networks) and learning paradigms (supervised, unsupervised, and reinforcement learning). Second, we discuss the technological pitfalls and dangers marketing managers need to be aware of when implementing AI in their organizations, including the concepts of badly defined objective functions, unsafe or unrealistic learning environments, biased AI, explainable AI, and controllable AI. Third, AI will have a deep impact on predictive tasks that can be automated and require little explainability, we predict that AI will fall short of its promises in many marketing domains if we do not solve the challenges of tacit knowledge transfer between AI models and marketing organizations.

本文通过知识创造和知识转移的角度讨论了人工智能在市场营销中的陷阱和机遇。首先，我们讨论“高阶学习”的概念，该概念将AI应用程序与传统建模方法区分开，在关注深度神经网络的最新进展的同时，我们涵盖了其基础方法（多层感知器，卷积和递归神经网络）和学习范式（监督学习，无监督学习和强化学习）。其次，我们讨论了营销经理在组织中实施AI时需要注意的技术陷阱和危险，包括目标功能定义不明确，学习环境不安全或不切实际，有偏见的AI，可解释的AI和可控的AI的概念。第三，