This paper outlines a practical pedagogical framework for integrating AI-driven analytics into marketing education, tailored to equip students for the fast-evolving industry. Central to this approach is an iterative model that adapts teaching strategies to keep pace with technological advancements and industry demands. The framework emphasizes practical application, steering curriculum development towards the inclusion of AI tools like machine learning and predictive analytics, and crafting experiential learning opportunities. A focused examination of current teaching methods reveals gaps and introduces actionable solutions for fostering analytical skills essential for the AI-enhanced marketing landscape. The model not only advocates for a balance between theory and practice but also addresses challenges such as resource accessibility and the necessity of ethical considerations in AI education. By promoting interdisciplinary collaboration and continual curriculum refreshment, the paper positions the model as an essential blueprint for nurturing future marketing professionals capable of leveraging AI analytics for strategic decision-making. The conclusion calls for academia-industry partnerships to further enrich marketing education and underscores the importance of this framework in preparing students for successful careers in AI-driven marketing.

本文概述了一个实用的教学框架，用于将人工智能驱动的分析整合到营销教育中，专门为学生提供适应快速发展的行业的能力。这种方法的核心是迭代模型，该模型可以调整教学策略以跟上技术进步和行业需求的步伐。该框架强调实际应用，引导课程开发纳入机器学习和预测分析等人工智能工具，并创造体验式学习机会。对当前教学方法的重点检查揭示了差距，并引入了可行的解决方案，以培养人工智能增强的营销环境所必需的分析技能。该模型不仅主张理论与实践之间的平衡，还解决了人工智能教育中资源可及性和伦理考虑必要性等挑战。通过促进跨学科合作和不断更新课程，该论文将该模型定位为培养未来能够利用人工智能分析进行战略决策的营销专业人员的重要蓝图。结论呼吁学术界与业界建立伙伴关系，进一步丰富营销教育，并强调该框架对于帮助学生在人工智能驱动的营销领域取得成功职业生涯做好准备的重要性。