Abstract: Algorithmic tacit collusion poses a serious challenge to the antitrust regulatory framework. Dynamic oligopoly theory suggests that such conduct is not merely an outcome of economic rationality but rather a product of deliberate human manipulation. Even in the absence of any interpersonal communication or contact among firms, algorithms can facilitate information exchange and behavioral coordination, thereby excluding or restricting competition. Antitrust intervention is therefore fully justified. Regarding regulatory approaches, it is essential to thoroughly explore the applicability of the three core pillars of antitrust law to algorithmic tacit collusion. The doctrine of collective dominance proves largely inapplicable due to misaligned regulatory logic, mismatched constituent elements, and excessively high thresholds for application. In contrast, both the prohibition of anti-competitive agreements and the merger control regime demonstrate potential applicability, yet each suffers from inherent limitations. To effectively address this issue, a comprehensive, end-to-end regulatory system—encompassing ex ante prevention, real-time monitoring, and ex post accountability—must be established. This can be achieved through measures such as creating a routine information-sharing mechanism, refining the criteria for identifying concerted practices, and developing monitoring systems specifically designed to detect algorithmic pricing behaviors, thereby enabling precise identification and effective regulation of algorithmic tacit collusion.