Translators Worldwide Face Income Plunge as AI Tools Erode Traditional Jobs
By Perplexity News Staff
LONDON – Artificial intelligence is reshaping the translation industry, slashing incomes and forcing professionals to reconsider their careers, as human translators grapple with a flood of machine-generated alternatives.
Timothy McKeon, a rare fluent speaker of the Irish language, once enjoyed steady work translating for European Union institutions. But the rise of AI tools that translate text and speech almost instantly has upended his livelihood. McKeon reports a staggering 70% drop in his income as EU opportunities dwindled, leaving him with offers to merely polish machine outputs—a task he refuses on principle, fearing it trains the very systems displacing his profession.[1]
“When the modified text is reintegrated into the translation system, it effectively ‘learns from your input,'” McKeon told CNN, highlighting how post-editing AI translations contributes to their improvement at humans’ expense.[1]
A 2024 survey by the United Kingdom’s Society of Authors underscores the crisis: more than a third of translators reported losing work to generative AI, which crafts sophisticated text, images, and audio from prompts. Alarmingly, 43% saw their earnings decline due to the technology.[1][2]
Global Ripple Effects
The disruption extends beyond Europe. In the United States, research by Karl Fre and Pedrolanos Parodes from the University of Oxford (covering 2010-2023) shows regions with heavy Google Translate usage experienced slower growth in translator jobs. Google’s shift to neural machine translation in 2016 made outputs more natural, accelerating the trend.[1]
Andy Benzo, president of the American Translators Association, confirms many U.S. translators are exiting the field amid shrinking demand.[2] Ian Giles, a translator and chair of the Translators Association at the Society of Authors, notes professionals are retraining because “translation isn’t generating the income it previously did.”[2]
Fardous Babbuh, a London-based Arabic translator and interpreter for international media including CNN, has seen written assignments evaporate. She blames AI alongside media budget cuts and is pursuing a PhD on how technologies are transforming the sector.[1]
Automated tools have drastically reduced workloads for human translators and interpreters globally, impacting job security and incomes, experts say.[1]
Broadening AI Job Threats
Translation is part of a larger pattern where AI targets knowledge-based roles. A report from the Centre for the Governance of AI and Brookings Metro identifies occupations with high AI exposure and varying adaptability. While about 37 million Americans face top-quartile AI risk, 70% possess skills for smooth transitions. However, roughly 6 million workers—often in clerical or administrative jobs held by women in smaller metros like university towns and Midwest markets—struggle with low adaptive capacity.[3]
Financial analysts, for instance, match office clerks in AI exposure but score 99% adaptability thanks to transferable skills and networks. High-resilience roles include web developers, marketing managers, and data scientists, while vulnerable ones lag.[3]
Sam Manning of GovAI warns of policy gaps: “If some share of this impact is job displacement… a core policy challenge is making workers more resilient.” He urges focus on financial resources, skills, and networks to mitigate inequality, in-work poverty, and child poverty.[2][3]
Calls for Support and Retraining
Experts decry insufficient government intervention. One researcher expressed worry that without aid for transitions, AI could exacerbate social divides.[2]
Many translators now pivot to adjacent fields, but the shift is painful. McKeon likens accepting AI post-editing to “digging your own professional grave,” as it entrenches machine dominance.[1]
The translation sector’s plight signals broader labor market shifts. As AI advances, policymakers, companies, and workers must adapt swiftly to avert widespread hardship.
This story draws on reports from CNN, the Society of Authors, University of Oxford research, and AI governance studies, reflecting trends as of early 2026.[1][2][3]