Introduction

The pervasive integration of Artificial Intelligence (AI) is not just an incremental technological update; it is a fundamental shift reshaping professional practices, academic delivery, and human communication itself. As this paradigm evolves, the fields of English for Specific Purposes (ESP) and English as a Medium of Instruction (EMI) find themselves at a critical intersection. Historically, both ESP and EMI have focused on preparing learners for real-world linguistic demands—be it the specialized discourse of a profession (ESP) or the content delivery in an internationalized academy (EMI). Now, these "real-world demands" are rapidly being redefined by machine capabilities
This conference, Lingua Futura: ESP, EMI and Artificial Intelligence, is dedicated to exploring this emergent triad. We move beyond simple questions of tool adoption to critically examine how AI is transforming the core knowledge, skills, and pedagogical models of language and content education. AI offers unprecedented opportunities for personalized learning, automated feedback, and access to vast, domain-specific linguistic data. Simultaneously, it presents challenges to traditional language roles, introduces ethical dilemmas regarding academic integrity and data privacy, and demands a fundamental re-evaluation of what constitutes effective teaching and learning in a language that is increasingly mediated and generated by algorithms.
We invite scholars and practitioners to join a crucial, forward-looking discussion. Our goal is to forge a path that not only adapts to AI but actively leverages its power to design a more effective, specialized, and equitable language education future. As noted by Lee and Lee (2023), the effective integration of these technologies requires a shift from viewing AI as a supplementary tool to recognizing its role as a "coconstructor of meaning" in professional and academic discourse.

Objectives of the Conference

• Critically examine how AI redefines linguistic needs in ESP and EMI contexts.
• Advance AI-driven pedagogical innovation in ESP and EMI curriculum design.
• Redefine the roles and competencies of ESP/EMI professionals and learners in an AI environment.
• Establish dialogue on the ethical, policy, and governance challenges of AI in academic language support.
• Formation des enseignants de langues dans les contextes scientifiques et techniques
• Forecast the essential language skills required for the professional and academic future ("Lingua Futura").

Tracks

• AI-Enhanced Needs Analysis & Curriculum Design: AI in diagnosing specific language needs and developing custom ESP curricula.
• Generative AI in ESP/EMI Content Creation: Utilizing Large Language Models (LLMs) to generate discipline-specific materials and learning resources.
• Intelligent Tutoring and Adaptive Learning: Developing and evaluating AIdriven systems for personalized ESP and EMI practice.
• AI, Assessment, and Academic Integrity: Tools for automated evaluation, feedback, and managing AI-generated output and plagiarism.
• Corpus Linguistics in the AI Era: Using AI and Natural Language Processing (NLP) for advanced professional discourse analysis and corpus building.
• EMI Instructor Development & AI Literacy: Training and upskilling content and language teachers in the effective and ethical use of AI.
• EMI Instructor Development & AI Literacy: Training and upskilling content and language teachers in the effective and ethical use of AI.
• Policy, Ethics, and Governance: Formulating institutional guidelines, addressing bias, and ensuring equitable access to AI tools.
• AI and Multilingualism in Higher Education: The role of AI in supporting translanguaging practices and balancing EMI with local languages.
• Professional Communication and AI: Investigating how AI reshapes workplace communication, specialized tasks, and the demand for soft skills.
• The Future of Human-AI Collaboration: Conceptual studies on the long-term impact of AI on learner autonomy and the evolution of specialized language competence.