Patent attorneys keep asking the wrong question. The question isn’t “machine translation or human translation” — that framing was already outdated by the time most firms started asking it. The real question is which category a document falls into before a single word gets translated, and right now, a lot of filing teams are answering that question with a coin flip disguised as a cost-saving decision. 🪙
What Post-Editing Actually Means Inside a Patent Filing
Post-editing sounds simple on paper: a machine produces a draft, a linguist cleans it up, everyone saves money. In practice, post-editing is a spectrum. Light post-editing fixes grammar and fluency so a document reads naturally. Full post-editing is supposed to bring the text to a standard indistinguishable from work done by a human translator from scratch. The problem is that almost nobody outside the language industry knows which version they’re paying for, and patent claim language has zero tolerance for the difference. A claim term that reads “close enough” to a patent examiner is not the same as a claim term that preserves the exact scope of protection the applicant filed for.
This distinction matters more in patent work than almost anywhere else in professional translation, because a patent claim is not prose — it’s a legal boundary drawn in words. Move that boundary by even one term, and the applicant either loses coverage they thought they had or gains coverage they never actually disclosed.
The Case That Should Worry Every Filing Team
There’s a real example that patent attorneys reference constantly, and it has nothing to do with machine translation specifically — it’s a warning about what happens when translated terminology drifts, however that drift occurs. In IBSA Institut Biochimique v. Teva Pharmaceuticals, the original Italian application used the term “semiliquido.” The U.S. filing translated it as “half-liquid” instead of “semi-liquid.” That single word choice became the center of the entire dispute. The Federal Circuit ultimately found the term indefinite, and the patent was invalidated. One translated word. An entire pharmaceutical patent.
Now apply that scenario to a workflow where a machine engine generates the first pass and a post-editor is instructed to preserve fluency over precision, working under deadline pressure, without patent-specific subject matter training. The IBSA case happened without AI in the loop at all — it shows how little room for error patent language actually has, even under fully human conditions. Add a machine-generated starting point and a rushed review pass, and the odds of a similar drift don’t go down. They go up. 📉
Where the Two Approaches Actually Diverge
| Risk Factor | Post-Editing (MTPE) | Human Translation from Scratch |
|---|---|---|
| Terminology consistency across claims | Depends on glossary quality fed to the engine | Built by a linguist who reads the full document first |
| Legal/technical nuance in claim scope | Often smoothed over for fluency | Actively interpreted and preserved |
| Risk of anchoring bias in review | Editor tends to trust the machine draft | No prior draft to anchor against |
| Speed | Faster | Slower |
| Cost per word | Lower | Higher |
| Suitability for prior art / internal review docs | Generally acceptable | Not necessary |
| Suitability for claims, specifications, prosecution filings | High risk | Recommended standard |
The table above isn’t an argument against post-editing as a category. It’s an argument against using it as a blanket policy across every document type a filing team touches, which is exactly what a lot of firms do once the cost savings on lower-stakes content look attractive.
Why the Industry’s Own Numbers Contradict the Sales Pitch
Adoption data tells its own story. Post-edited machine translation rose from roughly 26% of language service provider output in 2022 to nearly 46% by 2024, and more than 60% of providers now run over 30% of their projects through that model, according to Nimdzi’s 2025 industry survey. That growth is real and, for a huge share of business content, entirely justified. But patents are not marketing copy or internal documentation, and the same survey data that shows MTPE eating market share says nothing about whether that share includes the highest-stakes categories of legal and technical work.
Separately, a Steinbeis Institute study on international patent management found that 81% of professionals working with cross-border patents had personally encountered translation errors in applications, and more than one in four knew of cases where those errors seriously damaged an applicant’s ability to secure protection. Those numbers predate the current wave of MTPE adoption. There’s no reason to assume they’ve improved as speed-focused workflows have become the default rather than the exception.
Quality Scores Don’t Measure the Thing That Matters
The language industry has built an entire measurement culture around MTPE — similarity scores, edit-distance metrics, and newer “Time to Edit” benchmarks that estimate how long a linguist needs to bring a machine draft up to publishable quality. These are useful operational tools. None of them answer the only question a patent attorney actually cares about: is this text legally safe to file? A segment can score well on every fluency and efficiency metric available and still shift the scope of a claim in a way that only becomes visible during litigation, years later, when it’s far too late to fix. 🔍
The Filing Volume Behind the Pressure to Cut Corners
The pressure to speed up translation isn’t abstract — it’s a direct response to volume. International patent applications filed through the Patent Cooperation Treaty system reached 275,900 worldwide in 2025, marking a second consecutive year of growth, driven heavily by digital communication and semiconductor filings. A meaningful share of those applications still require translation at the national phase, since English-language publications made up less than half of total PCT filings in 2025, with Chinese, Japanese, Korean, and several other languages accounting for the rest. That translation demand isn’t shrinking, and it’s the exact pressure pushing filing teams toward faster, cheaper post-editing workflows — often without a formal policy distinguishing which documents can absorb that speed and which ones can’t. WIPO
A Routing Framework Attorneys Can Actually Use
Instead of treating this as an all-or-nothing vendor decision, a workable policy separates documents by what’s actually at stake:
| Document Type | Recommended Approach |
|---|---|
| Internal prior art review, competitive landscape scans | Post-editing is generally sufficient |
| Correspondence, internal memos, non-filing communication | Post-editing is generally sufficient |
| Patent claims and specifications for filing | Human translation by a subject-matter linguist |
| Priority document translations under Paris Convention or PCT national phase | Human translation, ideally reviewed by a second qualified linguist |
| Litigation exhibits, prosecution history, IPR/PTAB submissions | Human translation with certified accuracy attestation |
The line isn’t about budget. It’s about which documents will eventually be read by an examiner, a judge, or opposing counsel looking for exactly the kind of small inconsistency that turned “semiliquido” into a landmark invalidity ruling.
What This Actually Changes for Filing Strategy
None of this means machine translation has no place in a modern IP department — it clearly does, for the huge volume of lower-stakes content every legal team generates. The mistake is applying a single workflow decision uniformly across document types that carry wildly different legal consequences. A claim isn’t a product description, and treating it like one because the underlying technology looks similar is how filing teams end up relearning the IBSA lesson the hard way, one invalidated patent at a time. 🧾
(source: https://www.wipo.int)
(source: https://ipwatchdog.com)
(source: https://aeonlaw.com)