The Changing Face of Translation Competences and Qualifications in the AI Era: A Diachronic Analysis of Iranian Job Advertisements

Hajimohammadi, Mahdi; Salehian, Kiana

doi:10.22054/tir.2026.96898.1110

The Changing Face of Translation Competences and Qualifications in the AI Era: A Diachronic Analysis of Iranian Job Advertisements

Document Type : Original Article

Authors

Mahdi Hajimohammadi

Kiana Salehian

PhD Candidate in Translation Studies, Department of English Translation Studies, Faculty of Persian Literature and Foreign Languages, Allameh Tabataba’i University, Tehran, Iran

10.22054/tir.2026.96898.1110

Abstract

Open-access generative AI has transformed language-related industries. Few studies have examined shifts in the skills translators are expected to have from the pre-AI to the post-AI era. Using a diachronic approach, this study compared job advertisements published in the pre-AI (121) and AI eras (30). The study conducted a deductive content analysis of both datasets based on Li (2022). While both eras required linguistic competence, oral skills dominated the AI era. Psycho-physiological, extralinguistic, interpersonal, and translation knowledge competences became more relevant in the AI era. Overall, subtle shifts indicate that pure translation is less in demand. Furthermore, the demand for candidates with a translation degree slightly increased in the AI era. These findings can help novice translators entering the market, experienced translators updating their skills, and translation educators aligning curricula with current demands. Future research could use interviews to explore how AI has changed translators’ competences more directly.

Keywords

Translation competence

qualification

job advertisement

translation market

generative AI

Subjects