As artificial intelligence (AI) continues to advance, it brings with it significant privacy and ethical challenges—especially concerning group privacy. Traditional privacy frameworks have primarily focused on protecting individual privacy, but they struggle to address the complexities posed by AI systems that analyze and infer sensitive information from entire groups. This paper explores the unique risks to group privacy in AI, highlighting how AI’s ability to draw conclusions about communities, demographics, and social groups can lead to unintended discrimination, stereotyping, and privacy violations. We discuss various technical solutions, such as differential privacy, federated learning, and privacy-preserving technologies (PETs), that aim to safeguard group data while still enabling meaningful analysis. Additionally, we examine ethical considerations around fairness, accountability, and transparency, and propose guidelines to ensure that AI systems respect the privacy of groups. Finally, we discuss future research directions focused on improving AI systems’ ability to protect group privacy and developing more robust ethical frameworks for AI deployment across diverse sectors. By integrating both technological advancements and ethical principles, we believe AI can be harnessed to drive positive change without compromising the privacy and dignity of entire communities.