This paper examines how artificial intelligence (AI), machine learning algorithms, and automated digital systems shape linguistic practices, reinforce or challenge linguistic hierarchies, and influence communication in contemporary society. As digital platforms increasingly mediate human interaction, algorithms determine what content becomes visible, which linguistic varieties are privileged, and how users adapt their language to gain visibility and engagement. The study explores algorithmic bias in search engines, social media feeds, voice assistants, and automated moderation systems, highlighting how these technologies reproduce existing social inequalities related to class, caste, gender, and ethnicity. Drawing on sociolinguistic theories of language ideology, linguistic capital, and digital discourse, the paper argues that AI-driven communication environments are not neutral but deeply ideological. They shape linguistic norms, influence identity performance, and regulate public discourse. The findings underscore the need for critical sociolinguistic engagement with AI systems to ensure equitable, inclusive, and culturally sensitive digital communication.