Implementing AI-Powered Personalization in Marketing: A Case Study Analysis of Business Value and Consumer Acceptance

As technology continues to reshape the ways we live and connect, Artificial Intelligence (AI) has found a powerful role in transforming how businesses understand and engage with their customers. This thesis explores the use of AI-powered personalization in marketing—not simply as a tool for automation or efficiency, but as a dynamic way to create more meaningful, relevant, and timely interactions between companies and individuals. From recommender systems to predictive analytics and AI-driven chatbots, these technologies are becoming central to modern marketing strategies. But as these tools evolve, so do the questions they raise. What do consumers really feel about being “understood” by algorithms? Where is the line between helpful and intrusive? And how can companies deliver personalized experiences without compromising trust, transparency, or fairness? Drawing on theories like the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Personalization–Privacy Paradox, this thesis brings both technical understanding and human context into the conversation. Using real-world case examples and publicly available data from leading businesses across Europe and North America, this study seeks to understand not only what works in AI-powered personalization—but also why it matters. The goal is to uncover the delicate balance between innovation and ethics, automation and empathy, and to offer insights that help businesses build smarter, more respectful, and more human-centered marketing strategies.