This chapter presents an economic analysis of AI-enabled price discrimination (AIPD), particularly in digital markets. The concentration of Big Data and the use of analytical algorithms enable undertakings to predict each consumer’s willingness to pay with increasing accuracy, allowing them to offer personalized recommendations and tailored prices accordingly. Indeed, AIPD distinguishes itself from traditional price discrimination in offline consumer purchasing due to the neither universal nor transparent pricing mechanism based on algorithms. In economics, (AI-enabled) price discrimination is not always undesirable as it can increase static efficiency, and, on some occasions, it can promote dynamic efficiency and boost consumer welfare. Nevertheless, it may also lead to exclusionary and exploitative effects, especially once Tech Giants abuse their dominant positions in relevant markets. Since the protection of competition on the merits and consumer welfare are objectives of competition law in China and the EU, competition law seems to be a proper instrument to step into digital markets to address these concerns. Notably, price discrimination is explicitly mentioned in Article 102(c) of the TFEU and Article 22(1)(6) of the AML. Consequently, the following chapters will further discuss whether competition concerns—such as the exclusionary and exploitative effects of (AI-enabled) price discrimination in digital markets, among others—can also be effectively addressed.