Artificial intelligence is making language production easier, but it does not automatically make language learning deeper. When learners can generate sentences, essays, or ideas instantly, the risk is that thinking may be shortened while output becomes longer. This article approaches AI-supported language tasks from a linguo-cognitive perspective and asks a different question: not how AI helps students produce language, but how it can make them think through language. The paper argues that cognitive engagement emerges when learners question, reshape, and negotiate AI-generated content rather than consume it. AI is viewed not as a source of answers but as a stimulus for decision-making, reflection, and reasoning. Drawing on recent research in AI-assisted language learning and task-based pedagogy, the article highlights prompt design, adaptation of AI output, and iterative interaction as key pedagogical moves. AI-supported tasks become cognitively valuable when they slow learners down, require choices, and make reasoning visible. The article concludes that the real innovation of AI in language education lies not in automation, but in designing tasks where thinking cannot be outsourced.