Krashen’s Input Hypothesis, a foundational theory in second language acquisition (SLA), emphasizes the importance of comprehensible input slightly beyond a learner’s current proficiency level, or "i+1," as the key to language development. While the hypothesis has significantly influenced language pedagogy, its practical implementation often falls short in addressing the diverse needs of learners in traditional settings. Advances in artificial intelligence (AI) now present an opportunity to operationalize and expand this hypothesis in transformative ways. AI-powered tools, such as adaptive learning platforms and conversational chatbots, dynamically assess learner proficiency by curating personalized and progressively challenging input to support linguistic growth. Multimodal input delivery, through text, audio, video, and immersive simulations, further enriches learning by accommodating diverse cognitive styles and creating contextually meaningful experiences. Moreover, AI aligns with Krashen’s Affective Filter Hypothesis by reducing learner anxiety through gamified interfaces, immediate nonjudgmental feedback, and engaging, low-pressure practice environments. This article explores the integration of AI into Krashen’s theoretical framework and provides practical strategies for language teachers to enhance teaching practices and ensure human-AI synergy in classrooms. It also identifies key areas for future research, including the long-term efficacy of AI-enhanced input and its alignment with SLA principles. By merging AI’s capabilities with Krashen’s enduring ideas, this article reimagines the delivery of comprehensible input, bridging theoretical insights with technological innovations for modern language learning.