From Human to Hybrid: Artificial Intelligence and the Transformation of Language Services

Abstract

The growing presence of artificial intelligence (AI) in everyday life has generated debate regarding its impact on language services, where tools such as Large Language Models (LLMs) are increasingly being integrated. Framed as an exploratory and preliminary study, this article examines how a self-selected sample of 60 language-service professionals working in European contexts perceive the adoption of AI, particularly LLMs, in relation to professional practices, quality, ethical concerns, and emerging competence requirements. An embedded mixed-methods design was adopted, combining descriptive quantitative analysis with the thematic analysis of open-ended responses. The findings suggest a cautious and selective adoption of LLMs. While respondents recognise potential advantages related to speed, productivity, and support for specific tasks, they also identify persistent limitations concerning quality, terminology, contextual adequacy, cultural sensitivity, and the need for human revision. Respondents also report concerns about professional devaluation, changing work conditions, and the need for reskilling, particularly in relation to general translation and AI-assisted workflows. At the same time, some participants identify opportunities for innovation, enhanced human oversight, and the revaluation of specialised expertise. Overall, the study suggests that, from the perspective of the surveyed professionals, AI is contributing to the reconfiguration of language-service practices, while reinforcing the continued importance of human judgement, linguistic expertise, ethical responsibility, and critical engagement with AI-generated outputs.