Implementing generative artificial intelligence technologies in language industry workflows – A competence perspective

Abstract This article is concerned with the following question: Which competences are required by stakeholders who are tasked with implementing current generative artificial intelligence (AI) technologies (primarily in the form of uni- and multimodal large language models) in language industry workflows? To set the scene, the article first discusses briefly the ongoing AI saturation of the language industry. It then proceeds to discuss the concept of artificial intelligence literacy and shows how this concept has been operationalised for language industry contexts via a domain-specific AI literacy framework for translation, interpreting and specialised communication. In this context, the article also discusses potential AI literacy roles and competence levels that have been proposed in the literature and briefly sketches how these may be related to the domain-specific AI literacy framework. Then, the article zooms in on the implementation dimension of the framework. For each subdimension of this dimension, it proposes a draft competence descriptor and discusses in detail the relevant aspects of generative AI implementation subsumed under these subdimensions from a competence perspective. The article concludes with a brief outlook on how domain-specific AI literacy may help stakeholders navigate the further evolution of the language industry under the impact of high-performing AI technologies.