Abstract This article examines recent developments in lexicography driven by artificial intelligence (AI) and digital tools, situating contemporary dictionary-making within the broader framework of digital humanities. Rather than offering a comprehensive survey, the study adopts a selective, example-driven meta-analytical approach, focusing on representative tools, projects, and strands of specialist literature that exemplify broader methodological shifts in the field. Drawing on cases such as AI-assisted workflows in learner lexicography and corpus-based tools including Sketch Engine and Lexonomy, the article explores how computational methods support definition drafting, corpus analysis, bilingual lexicography, and user-oriented adaptation. At the same time, it critically addresses limitations related to data scarcity, algorithmic bias, transparency, and the uneven accessibility of AI technologies, particularly in low-resource contexts. The analysis argues that current advances do not replace lexicographic expertise but reconfigure it, reinforcing the need for hybrid human-AI models in which editorial judgment, cultural knowledge, and ethical responsibility remain central. By foregrounding both technological potential and structural constraints, this study contributes to ongoing debates in digital scholarship on how AI reshapes lexicographic practice, professional roles, and the stewardship of linguistic knowledge.
Khoa Nguyen-Viet (Fri,) studied this question.