This research delves into the linguopragmatic characteristics of communicative practice between humans and chatbot GPT. The research explores the evolving dynamics of human–machine communication through a detailed analysis of dialogic interactions, semantic coherence, and pragmatic connectivity in German and Russian languages. Drawing on linguistic theories and computational models, the research highlights the structural and semantic cohesion of stimulating turns and reaction turns in dialogues, shedding light on the intricate nature of communication with chatbots. The research also examines the cognitive mechanisms involved in interpreting speech acts, such as implicature, presupposition, and entailment, within human-chatbot interactions. By investigating the functional roles performed by neural network chatbots, the authors aim to elucidate the specificity and correlation of communication practices in the realm of artificial intelligence. Furthermore, the analysis delves into the application of Gricean maxims in designing analytical conversational behavior for chatbots. The research underscores the relevance of further research to refine linguocognitive models for chatbots, enhancing the efficacy of communicative interactions.