Interpreters and Translators: daily tasks & AI impact
This page breaks Interpreters and Translators into the top 15 daily O*NET tasks and scores each for Generative AI automation probability. Those task scores roll up to an overall vulnerability index of 63/100 (Moderate automation risk). Struck-through rows are ≥80% automatable; highlighted safer rows are under 30% or primarily physical.
High-automation exposure
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Durable human work
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.
| Task | Importance | AI probability | Nature |
|---|---|---|---|
| Follow ethical codes that protect the confidentiality of information. Core | 4.86 | — | — |
| Translate messages simultaneously or consecutively into specified languages, orally or by using hand signs, maintaining message content, context, and style as much as possible. Core | 4.73 | — | — |
| Listen to speakers' statements to determine meanings and to prepare translations, using electronic listening systems as necessary. Core | 4.48 | — | — |
| Compile terminology and information to be used in translations, including technical terms such as those for legal or medical material. Core | 4.45 | — | — |
| Adapt translations to students' cognitive and grade levels, collaborating with educational team members as necessary. Supplemental | 4.42 | — | — |
| Refer to reference materials, such as dictionaries, lexicons, encyclopedias, and computerized terminology banks, as needed to ensure translation accuracy. Core | 4.41 | — | — |
| Check translations of technical terms and terminology to ensure that they are accurate and remain consistent throughout translation revisions. Core | 4.35 | — | — |
| Identify and resolve conflicts related to the meanings of words, concepts, practices, or behaviors. Core | 4.3 | — | — |
| Check original texts or confer with authors to ensure that translations retain the content, meaning, and feeling of the original material. Supplemental | 4.3 | — | — |
| Compile information on content and context of information to be translated and on intended audience. Core | 4.24 | — | — |
| Adapt software and accompanying technical documents to another language and culture. Supplemental | 4.23 | — | — |
| Educate students, parents, staff, and teachers about the roles and functions of educational interpreters. Supplemental | 3.96 | — | — |
| Proofread, edit, and revise translated materials. Supplemental | 3.93 | — | — |
| Train and supervise other translators or interpreters. Supplemental | 3.8 | — | — |
| Read written materials, such as legal documents, scientific works, or news reports, and rewrite material into specified languages. Supplemental | 3.71 | — | — |
What remains human
No tasks currently fall under the safe threshold for this occupation.
FAQ
Which Interpreters and Translators tasks are most exposed to AI?
No task in this set currently exceeds the 80% threshold, so risk is spread across moderate probabilities rather than a few catastrophic duties.
Which Interpreters and Translators tasks are safest from Generative AI?
This profile has little “safe” task mass under our thresholds. Workers should treat AI fluency as mandatory and actively map transferable skills into lower-risk roles.
How should I read the Interpreters and Translators task table?
Importance comes from O*NET incumbent ratings. Automation probability is model-generated for current Generative AI capability (not speculative AGI). Digital / physical / mixed labels describe the modality of the work, which strongly correlates with near-term automation potential.