The rapid integration of artificial intelligence into translation and interpreting practice is transforming both professions and reshaping translator and interpreter education. While neural machine translation, generative AI and technology-assisted interpreting tools have significantly enhanced linguistic accuracy, efficiency and accessibility, they continue to face challenges in interpreting cultural nuances, implicit meanings, pragmatic conventions and audience expectations. Against this backdrop, this paper argues that intercultural competence (IC) is not simply another component of translation and interpreting competence (Karras, 2025; Prieto Ramos, 2024) but one of the defining human attributes that distinguishes language professionals from algorithmic systems.
Drawing on established models of translation competence, including the Process in the Acquisition of Translation Competence and Evaluation model and the European Master's in Translation framework, together with research on intercultural competence, the presetation examines the role of translators and interpreters as intercultural mediators (Federici, 2011) rather than mere language converters. It discusses the distinction between intercultural awareness and intercultural competence, arguing that effective and appropriate translation and interpreting require informed cultural judgement, ethical decision-making and contextual adaptation, which are areas where human expertise remains indispensable despite recent advances in generative AI (Bowker, 2025; Ramírez-Polo & Vargas-Sierra, 2023)
The paper further explores the implications of this reality for translator and interpreter education. Although intercultural competence is widely acknowledged as essential, research suggests that it is often addressed implicitly rather than systematically within translation and interpreter training programmes. This presetation therefore argues that intercultural competence should be addressed more explicitly within translator and interpreter education and training programmes through authentic translation and interpreting tasks, cultural comparison activities, reflective practice, audience-oriented translation projects and AI-assisted translation workflows. Rather than positioning AI as a threat to translator and interpreter education, the paper advocates a complementary human–AI partnership in which technological literacy is developed alongside intercultural, ethical and critical competences (Bowker, 2025; Prieto Ramos, 2024).
It concludes that, in the era of algorithmic language mediation, the future of translator and interpreter education lies not in competing with artificial intelligence but in cultivating the uniquely human capabilities that enable language professionals to negotiate meaning across languages, cultures and communicative contexts.
Ioannis Karras is a Professor in the Department of Foreign Languages, Translation and Interpreting, Faculty of Humanities, at Ionian University, Greece. He holds a B.A. in English and a B.A. in Linguistics from the University of Calgary, Canada; an M.Ed. in Teaching English as a Foreign Language (TEFL) from the Hellenic Open University, Greece; an M.Sc. in Intercultural Communication from the University of Warwick, UK; and a Ph.D. in Applied Linguistics from the National and Kapodistrian University of Athens, Greece. Professor Karras has lectured as a visiting professor and invited speaker at universities around the world. He has extensive teaching experience in Applied Linguistics, English as a Foreign Language (EFL) Teaching Methodology, and Intercultural Communication at undergraduate, postgraduate, and doctoral levels. He has delivered numerous presentations at international conferences and has conducted seminars and workshops for national and international audiences. He has also (co-)authored several books, book chapters, and articles published in international journals and conference proceedings in his areas of expertise.
