Foreign Language Training in the Age of Big Data and Artificial Intelligence: An Approach to Diplomatic Training

Purpose – The integration of Artificial Intelligence (AI) and Big Data analytics into diplomatic and foreign foreign language training has the potential to revolutionize pedagogical approaches, enhancing discourse analysis skills in international relations. However, there remains a gap in understanding how AI-driven tools and data analytics can be systematically implemented in diplomatic training programs. This paper examines Natural Language Processing applications in diplomatic discourse analysis and foreign language education, with a particular focus on the Diplomatic Academy of Vietnam. Design/methodology/approach – The study employs a mixed-methods approach, including sentiment analysis and topic modeling of U.S. and Chinese diplomatic statements in 2024, a survey of 100 students and young diplomats, and in-depth interviews with ten diplomatic experts. Computational tools, including Natural Language Processing techniques, were used to analyze large-scale diplomatic discourse data. Findings – The analysis reveals distinct patterns in diplomatic rhetoric, highlighting shifts in sentiment and topic emphasis over time. Survey results indicate strong support for AI-driven language learning and negotiation simulations, while expert interviews underscore the need for ethical AI governance and human oversight in diplomatic training. Additionally, findings suggest that AI-enhanced learning methods improve foreign language acquisition and discourse comprehension but require careful integration to align with traditional diplomatic competencies. Originality/value – This is one of the first studies to comprehensively examine the intersection of AI, Big Data, and diplomatic training, providing empirical insights into the effectiveness of AI-driven methodologies. The study also offers policy and educational recommendations for institutions like the Diplomatic Academy of Vietnam to enhance AI integration in training programs.