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Translator / Interpreter
Moves meaning between languages — and decides what to do when the meaning does not move cleanly.
Find the actual certification requirement in your market and write down the cost, the time and who accepts it. Most people never do this and assume it is harder than it is — or easier.
This is not a probability of losing your job. It combines how much of the role's task load is exposed to automation with how far adoption has actually gone — useful for comparing occupations on one consistent basis, and for nothing else.
Written for general commercial translation. Certified legal, medical and simultaneous conference interpreting sit on materially different curves, mostly because of liability and real-time constraints; court, medical, conference and sign-language interpreters have their own page.
What is actually changing#
The unit of analysis is the task, not the job title. A role is not replaced — its task mix shifts.
Each tile is one task. Its size is how much of the job it is; its colour is where the task is heading. Click a tile to see what the judgement does not establish.
Quality is highly uneven across language pairs and domains. Low-resource pairs and specialised terminology remain much weaker than the headline impression suggests.
It is real work, but it is usually priced per word at a fraction of translation rates. More of the industry's hours, less of its income.
Certification protects the signature, not the volume of work behind it. Expect the same documents to need a named certifier at a fraction of the hours, which is a pay structure change more than a job count change.
Transcreation is a small, high-end slice of a market whose bulk is volume translation. Being safe in this slice says nothing about whether there is room in it for the translators displaced from the rest.
The preference for an accountable human is strongest in exactly the settings that are rarest — courts, clinics, negotiations. Routine interpreting, which is most of the hours, has fewer defenders.
Is this your job? Say so and this page narrows to your share of it.
A job title is a bundle of tasks bought together, and no two people hold the same bundle. Nothing is sent anywhere — it stays in this browser.
Read all 5 tasks in full — direction, reasoning and limits →
Recent changes#
Mainland China, the association's own industry census. Against its 2025 report (2024 data: 70.8 billion yuan output, 6.808 million workers), the workforce rose about 0.9% while output fell about 1%. The headline workforce number is roughly six times the 1.135 million counted as full-time translators, so most of it is not full-time work. The same report puts 2,183 firms with AI translation as their main business and calls human-machine collaboration the industry's basic consensus; the 2024 report had already said over 90% of firms were deploying large models.
Verifiable change in hiring, headcount, hours or job scope. Highest weight — but causal attribution still has to be argued, not assumed.
One line in a shareholder letter, stated in the present tense: "In content production and promotion, we're using AI to improve subtitle localization, making it easier for our titles to reach more viewers around the world." Netflix does not say which languages, what share of titles, which step of the pipeline, or whether any human localiser's work changed. "Improve" is the company's word and could mean a tool handed to translators as easily as a draft generated without one. Subtitles only — the letter says nothing about dubbing.
An employer has put it into production. Can move the baseline — weighted by scale and how similar the setting is.
Entertainment subtitling, one streaming platform, one episode (Necronomico and the Cosmic Horror Show, ep. 1, 1 July 2025). The company's president had said in 2024 it was testing generative AI for subtitling; the failure was unreviewed vendor output.
Failure, rollback, regulation or cost is suppressing adoption. Can lower an assessment or widen its uncertainty.
One company's stated policy for contractor work (content and translation). Primary source is a LinkedIn post by the company.
Verifiable change in hiring, headcount, hours or job scope. Highest weight — but causal attribution still has to be argued, not assumed.
United States, health programs receiving federal funds. The final rule says that when translation services are required, a covered entity must utilize the services of a qualified translator, and that if it uses machine translation when the underlying text is critical to an individual's rights, benefits or meaningful access, when accuracy is essential, or when the source contains complex, non-literal or technical language, the translation must be reviewed by a qualified human translator. Effective July 5, 2024. It is one country's rule for health programmes; other parts of the rule have been challenged in court.
Regulation, subsidy or public procurement is requiring or funding adoption — the mirror of a constraint. It shows adoption is being required, not that it has happened, so one mandate is never enough on its own; two independent ones are.
The entry is the department's own submission to the statutory inventory OMB publishes under the Advancing American AI Act, so the publisher is the employer describing a deployment it runs. The department draws the line itself: the machine output is a tool for initial review by an attorney and, in its own words, does not constitute an official record. The entry gives its operational date only as a month, 03/2019, so it is recorded as the first of that month; the reported date is the April 2026 data upload, which the repository dates as of 13 April 2026. Read across the whole file, the same product appears inside this one department at four bureaus deployed (department-wide from 03/2019, the antitrust division from 01/2023, the criminal division and the public affairs office from 01/2024), one bureau not yet deployed, and one retired. A second agency, the Federal Trade Commission, records the same product deployed since 2022 and gives its reason as manual translation and transcription being slow and of inconsistent accuracy. What the entry does not give is any headcount, any volume, or any measure of how review time changed. It also says nothing about certified translation: it describes an initial read, not an official one, so it does not bear on who signs a certified document.
An employer has put it into production. Can move the baseline — weighted by scale and how similar the setting is.
What this means for you#
This is the hardest first-batch occupation to enter right now. The volume work that used to let a new translator build speed and a portfolio is largely gone, and post-editing rates are too low to learn on. If you are entering, aim at a specialism with liability or regulation attached, or at localisation roles that sit inside a product team rather than at an agency.
Your per-word income is under structural pressure and that is unlikely to reverse. The defensible positions are subject-matter authority, certification, and client relationships where you are advising on the market rather than delivering words. If your current mix is mostly volume work at agency rates, treat that as a signal to move rather than to work faster.
Your options#
Four directions, each with its real constraints and one thing you can test this week. Continuing as you are is a legitimate choice — it just has to be a chosen one.
Specialise into a liability-bearing niche
Certified legal, medical and regulatory translation still needs a named, qualified person, and prices accordingly.
Certification takes real time and money, and requirements are jurisdiction-specific. Verify the exact local requirement before starting.
Find the actual certification requirement in your market and write down the cost, the time and who accepts it. Most people never do this and assume it is harder than it is — or easier.
Localisation inside a product team
In-house localisation is about making a product work in a market — terminology systems, cultural review, working with engineers — and is paid as a product role rather than per word.
Requires comfort with tooling and version control, and usually a specific target market where you are genuinely native.
Take a product you use, find three localisation errors in your language, and write up why each one is wrong. That document opens doors.
User research or international operations
The underlying skill — understanding what people in another market actually mean — is the scarce part, and it is worth more when applied to research than to text.
The title change makes your CV harder to read. Expect to need one project that demonstrates the new skill before anyone will hire you for it.
Interview three users in your language about a product, and write a one-page findings note. That is the artefact, and it takes a week.
Reposition from translating to advising
Clients still need someone to tell them whether the message works in the target market. That conversation is not priced per word.
Only works with clients who have a market decision to make. Agency intermediation usually blocks it.
On your next job, send one unsolicited paragraph on what will not land in the target market and why. See whether the client engages.
Common questions#
Studying a language is not the same as training to be a translator, and the two have diverged sharply. Deep command of a language plus a second domain — law, medicine, product, research — is more valuable than ever. Training aimed purely at producing translations is aimed at the part of the work that has moved fastest. If you are already in the programme, the useful move is to add the second domain now rather than to switch out.
We will not give you a date, and anyone who does is guessing. Watch one thing instead: what your clients pay for. The moment a regular client asks for post-editing rates rather than translation rates, the change has arrived at your desk — that repricing is the event, and it usually comes a year or more before any volume drops.
First-draft translation of routine text — that is the task on this page marked automating, and it is where most working hours and most invoice lines sit. Certification, transcreation and live interpreting are not in the same position, but together they are a smaller and more senior market than the volume work they would have to absorb.
Unevenly, and that unevenness is the most useful thing to know. Machine quality is strongest between high-resource European languages and weakest on low-resource pairs and specialised terminology. If you work in a pair with little training data, your exposure today is genuinely lower — and it is also the thing most likely to change without warning when someone releases a model trained on more of your language.
Studying towards this?
These majors lead here. Their pages break down which of their competencies transfer and what graduates typically lack.
What these judgements rest on#
3 of 5 task judgements on this page are backed by a verified event and 2 are platform inference, each labelled where it appears. Behind them sit 1 technology dimensions, a reconstructed trajectory since language models reached the public, and 6 verified events.
See which technologies, how it got here, and the method →
Where it sits in the official classification: skills, knowledge, related jobs →
Other roles in the same function#
A company divides its work into functions before it divides it into jobs. These sit in Core delivery (industry-specific) alongside this one — a fact about org charts, not a judgement that they are similar or that they are changing in the same direction.
Content moderator · Registered nurse · Midwife · Radiologist · Pathologist · Radiographer / radiologic technologist · General practitioner / primary care doctor · Surgeon · Anaesthesiologist / anaesthetist · Respiratory therapist · Optometrist · Care worker / nursing assistant · Counsellor / psychotherapist · Psychologist · Dietitian / nutritionist · Pharmacist · Pharmacy technician · School teacher · Driving instructor · University lecturer · Chef / cook · Electrician · Plumber · HVAC technician · Architect · Building inspector · Drafter / CAD technician · Interior designer · Civil / structural engineer · Land surveyor · Urban planner · GIS analyst / cartographer · Electrical engineer · Chip design engineer · Mechanical engineer · Industrial engineer · Quantity surveyor · Journalist · Editor and proofreader · Interpreter · Retail cashier / shop assistant · Bank teller · Medical assistant / clinic assistant · Waiter / restaurant server · Bartender / barista · Hairdresser / barber · Construction worker · Bricklayer / blocklayer · Carpenter / joiner · Auto mechanic / vehicle technician · Medical laboratory technician · Physiotherapist / rehabilitation therapist · Speech-language pathologist / speech and language therapist · Occupational therapist · Phlebotomist · Massage therapist · Firefighter · Paramedic / EMT · Police officer · Emergency dispatcher · Farmer · Gardener / landscaper · Social worker · Dentist · Dental hygienist · Dental assistant / dental nurse · Veterinarian · Librarian · Welder · Machinist / CNC machinist · Sonographer