Ten Years from Google Translate to ChatGPT: Why Machine and AI Legal Translation Carries Severe Consequences for Clients and Lawyers

By John O’Shea (LL.B. (Hons), LL.M.)

1. A Decade of Technological Evolution, The Same Underlying Hazard

Across commercial law firms, corporate legal departments, and private litigation, a quiet assumption has taken hold that pasting foreign-language correspondence, witness statements, statutory provisions, or commercial agreements into a machine translation engine or generative AI chatbot carries no real consequence. Users frequently rationalise this practice by telling themselves that the output is merely for preliminary orientation, internal comprehension, or an informal check before instructing external counsel.

Empirical research into legal workflows confirms how deeply entrenched this attitude has become. In a survey of practising lawyers in Greece that I co-authored with Kyriaki Kourouni in Revista Tradumàtica (2025), practitioners reported turning to machine translation primarily to grasp the basic meaning of foreign texts (9.28%), manage cross-border client communications (8.25%), review internal documents (7.22%), and examine draft commercial contracts (6.19%). Strikingly, whilst 35.72% of the surveyed lawyers recognised that uploading legal material into free online translation tools breaches client confidentiality, 0% of respondents expressed any fear of being sued for professional malpractice or legal liability as a consequence of relying on machine output.

A decade of case law across common law and civil law jurisdictions demonstrates that this complacency is misplaced. Ten years ago, litigants who placed unverified Google Translate outputs before tribunals watched their evidence get rejected and their claims fail because statistical machine translation produced visibly broken syntax. Today, ten years down the line, the transition to neural machine translation (NMT) and large language models (LLMs) such as ChatGPT has failed to eliminate the underlying jurilinguistic hazard. By replacing obvious syntactic incoherence with polished, authoritative-sounding prose, modern artificial translation has made substantive errors far harder to detect, expanding the fallout to encompass both the client whose substantive rights are compromised and the legal practitioner whose professional conduct comes under judicial or disciplinary scrutiny.

2. Why Fluent AI Output Traps Both Clients and Counsel

To understand why modern AI translation creates acute legal exposure, one must look at how language models process legal text. In earlier generations of machine translation, defective output announced itself through garbled grammar that immediately warned a careful lawyer or company director to treat the text with caution. As Juliette Scott and I demonstrated in our Legal Translation Vulnerability Scoping framework (Research Handbook on Jurilinguistics, Edward Elgar, 2023), neural networks and generative AI replaced that visible awkwardness with an illusion of fluidity.

Machine learning systems optimise for probabilistic plausibility rather than comparative legal equivalence. When translating between legal orders that do not share the same conceptual architecture, such as the continental European civil law tradition of Greece and the common law systems of England and Wales or the United States, surface fluency masks severe doctrinal distortions. In our chapter Words Matter: How AI Pollutes the Language of the Law (International Handbook of Legal Language and Communication, Springer Nature, 2026), Argyri Panezi and I analysed how English-dominated training corpora introduce systematic jurisdiction bias and technology-mediated legal transplants into translated legal texts.

Empirical studies of Greek-to-English and English-to-Greek AI outputs illustrate how easily these systems flatten or displace statutory concepts:

• Criminal and Regulatory Classification: In Greek criminal and regulatory compliance matters, automated systems routinely collapse the statutory tripartite division of offences under the Greek Penal Code (κακούργημα, πλημμέλημα, and πταίσμα) into generic English words such as “crime” or “offence”, or import Anglo-American common law concepts by rendering δόλος (dolus) as mere “intent” and αναστολή ποινής (suspension of sentence) as “probation”.

• Civil and Corporate Acts: In civil and commercial contexts, neural translation systems have rendered a private-law legal transaction or juridical act (δικαιοπραξία) as “jurisdiction” (δικαιοδοσία), and reduced a formal criminal complaint subject to strict statutory time limits (έγκληση) to an informal “report”.

• Appellate and Procedural Finality: As Daniel Webber and I documented when translating the Greek procedural codes (Translating Greece’s Procedural Codes, ELETO, 2023), even traditional legal dictionaries and automated tools routinely flatten the distinct procedural stages of Greek court decisions into the single English phrase “final judgment”. Under the Greek Code of Civil Procedure, however, an οριστική απόφαση disposes of the action before the first-instance court whilst remaining subject to ordinary appeal, a τελεσίδικη απόφαση denotes a judgment where ordinary appellate remedies have been exhausted or expired, an ανέκκλητη απόφαση refers to a decision that is by law not amenable to ordinary appeal, and an αμετάκλητη απόφαση signifies an irrevocable judgment no longer open to cassation before the Hellenic Supreme Court (Areios Pagos). A translation that renders all four categories simply as a “final judgment” misleads foreign counsel on the fundamental question of whether a judgment can still be challenged or enforced.

Furthermore, as Pierre Moor (2026) has observed in the context of legal interpretation, statutory and contractual provisions frequently contain deliberate normative ambiguity or open-textured concepts whose scope must be resolved by a court rather than a translator. When a generative AI model encounters an ambiguous source provision, it silently selects the most statistically probable English phrasing, committing the reader to a single substantive interpretation without alerting counsel that the original text admitted more than one reading.

Nor can this problem be solved simply by asking a reviewer to “post-edit” machine output. As Vilelmini Sosoni, Maria Stasimioti, and I demonstrated in our empirical comparison of from-scratch human translation and machine translation post-editing (Journal of Language and Law, 2022), the grammatical smoothness of neural output primes even trained reviewers to overlook major terminological and accuracy errors, creating a false sense of security whilst shifting full professional liability onto the human who signs off on the text.

3. Ten Years of Machine Translation in the Courts: From Early MT to Modern AI (2016–2026)

If technological progress had solved the risks of automated legal translation, judicial decisions criticizing defective machine translations would have faded into history after the mid-2010s. Instead, the case law from 2016 to 2026 shows a continuous line of evidentiary failures across tax tribunals, commercial courts, and statutory tribunals.

The 2016 Benchmark: Rejected Evidence and £243,564 in Tax Liability

Ten years ago, two decisions before the UK First-tier Tribunal (Tax Chamber) illustrated the immediate financial and procedural cost of relying on unverified translations in cross-border proceedings:

• KIP UK Ltd v Revenue and Customs [2016] UKFTT 821 (TC): In a customs duty dispute, a party sought to rely on English translations generated through Google Translate. The Tribunal upheld the opposing party’s formal objection to the evidence, ruling that the machine translation “did not produce any meaningfully comprehensible summary” upon which a judicial body could rely.

• Essential Telecom Ltd v Revenue and Customs [2016] UKFTT 475 (TC): In a cross-border value-added tax dispute involving £243,564, HM Revenue and Customs relied on unverified translations of Italian Guardia di Finanza investigation reports concerning an Italian counterparty. The UK Tribunal refused to admit the disputed evidence, characterising it as double hearsay and finding that the defective translations had caused “many wrong assumptions about the corporate or non-corporate form of the counterparty”.

Ten Years Later: NMT and ChatGPT in Commercial and Statutory Litigation

Move forward a decade to the era of neural machine translation and generative AI, and litigants are encountering the exact same judicial wall, now compounded by AI fabrication:

• Euroboor BV v Grafova: In commercial litigation before a United States court, a party submitted a Google Translate version of a Dutch court judgment on which its legal argument relied. Despite a decade of neural network upgrades since 2016, the American court struggled to decipher the judicial reasoning in the machine-translated Dutch judgment, demonstrating that raw MT remains incapable of conveying complex foreign judicial reasoning to a common law bench.

• Lozano González v Roberge: Before a Canadian tribunal, a litigant relied on a ChatGPT translation of foreign statutory provisions to support their legal case. Upon scrutiny, the tribunal found that ChatGPT had not merely translated the legislation inaccurately; the chatbot had effectively rewritten the statutory provisions on which the litigant’s argument depended.

This phenomenon of statutory distortion aligns directly with the empirical test reported in Panezi & O’Shea (2026), where ChatGPT, queried in English regarding a civil dispute under Greek law, fabricated confident English translations and doctrinal interpretations of Articles 1003 to 1010 of the Greek Civil Code. Across the globe, more than 2,000 judicial decisions have now documented the submission of AI-fabricated legal authorities and distorted statutory texts, a trend that has begun to trigger direct commercial litigation against AI vendors themselves, such as Nippon Life v OpenAI (filed in March 2026).

4. Consequences for the Client: Substantive Loss and ‘Terminology Drift’ in Commercial Disputes

For corporate and private clients, the danger of casual or uncoordinated translation extends well beyond a single rejected exhibit. Commercial relationships and cross-border investments evolve over many years. Agreements are negotiated and signed, board minutes and financial disclosures under Greek Law 4548/2018 are recorded, correspondence is exchanged when commercial friction arises, and extrajudicial notices are served when the relationship breaks down.

A recent decision of the Hellenic Supreme Court, Judgment No. 221/2026, provides a textbook demonstration of how translation choices made at different stages of a commercial venture can become a central forensic issue in high-value litigation.

The dispute arose out of a long-running wind-energy project in Greece between a Greek project developer and a Spanish corporate investor. Although the wind-energy project was situated in Greece, the commercial relationship between the parties was governed by contracts drafted in English. When the commercial relationship broke down, the Spanish investor served an extrajudicial notice declaring that it had decided to “terminate the … Contracts and withdraw from the Project”, proposing to transfer its shares in the project company for a nominal consideration pursuant to Article 5.2 of the Framework Agreement.

When the dispute reached the Greek courts, the legal characterisation and validity of that notice turned heavily on how the English contractual terms had been translated into Greek across the documentary record:

1. Inconsistent Rendering of the Core Contractual Mechanism (“Withdrawal”): In translating the Framework Agreement, the Greek developer rendered the heading “Withdrawal” as Υπαναχώρηση (the Greek civil law concept of statutory or contractual rescission/withdrawal). The Spanish investor’s translation of the heading used the more general word Απόσυρση, yet within the operative clauses of the Spanish investor’s own translation, the phrase “withdraw from their obligations” was rendered using υπαναχώρηση, while a third variant, αποχώρηση (departure/exit), also appeared in the arguments. The Court of Appeal expressly noted this terminological inconsistency across the translations before concluding, from the contractual mechanism of the share transfer, that “withdrawal” operated in Greek law as contractual υπαναχώρηση.

2. Disputed Translation of Commercial Thresholds (“Feasibility”): Under Article 3.5 of the Project Agreement, the investor’s right to withdraw was conditional upon the project’s “technical and financial feasibility” proving insufficient. One translation rendered “feasibility” as βιωσιμότητα (viability/sustainability), whereas the Court of Appeal held that σκοπιμότητα (expediency/feasibility in context) was the appropriate rendering within the architecture of the clause. Ultimately, the courts found that the investor’s notice failed to specify whether the alleged inadequacy was technical, financial, or both, and failed to identify the supporting data, resulting in the dismissal of the investor’s cassation appeal before the Supreme Court.

Hellenic Supreme Court Judgment No. 221/2026 illustrates what happens when translation is treated as an isolated lexical exercise rather than a file-level legal strategy. When a corporate client or legal team feeds a newly received extrajudicial notice, board resolution, or commercial letter into an AI tool or commissions an ad hoc translation without cross-referencing the terminology established years earlier in the underlying framework agreement, terminology drift enters the file. Because generative AI translates probabilistically, it will readily render an ordinary-looking English word like “withdrawal”, “feasibility”, “material”, or “default” using one Greek synonym in 2021 and a different Greek term in 2026. Once those documents are placed side by side before a court, the client has to pay counsel to litigate avoidable ambiguities created by their own translations.

5. Consequences for the Lawyer: Judicial Criticism, Disciplinary Exposure, and Malpractice

While clients bear the commercial and substantive fallout of defective translations, recent decisions from 2025 and 2026 demonstrate that practising lawyers face acute reputational, procedural, and disciplinary exposure when AI-translated material enters a legal file.

Judicial Rebuke for Overlooking AI Provenance: AA v Secretary of State for the Home Department [2026]

In AA v Secretary of State for the Home Department [2026] UKFTT PA747122024 (IAC), an appellant’s solicitors filed an English witness letter in support of an asylum appeal before the UK First-tier Tribunal (Immigration and Asylum Chamber). The English text read fluently and appeared to support the appellant’s factual account. However, at the end of the witness letter sat a conspicuous sentence offering to turn the letter into a formal affidavit, insert notarisation language, or make the wording more neutral.

First-tier Tribunal Judge CJ Williams immediately recognised the sentence for what it was: a conversational follow-up prompt generated by a chatbot. Upon questioning by the judge, the witness explained that he had written his account in Arabic, used ChatGPT to translate it into English, and then asked his daughter to compare the English output against the Arabic original to check that the meaning was the same.

At paragraph [28] of the judgment, Judge Williams delivered a pointed observation directed at the legal representatives who had placed the document into the court bundle:

“It is unfortunate that it fell to the Tribunal to notice this.”

For litigation solicitors and counsel, AA exposes two distinct professional vulnerabilities:

• Failure of Basic Document Control: Detecting the leftover ChatGPT prompt at the foot of the witness statement required no knowledge of Arabic. It required only that the legal team read the English exhibit carefully from start to finish before filing it with the Tribunal.

• The Fallacy of Casual ‘Human Involvement’: When lawyers defend the use of AI translation, they frequently point to the presence of a “human in the loop”. In AA, the witness’s daughter had reviewed the ChatGPT translation against the Arabic original. Yet as the case demonstrates, the mere fact that a bilingual relative, client employee, or junior staff member has looked over an AI translation tells a court nothing about their competence to identify subtle shifts in evidentiary certainty, omitted qualifications, or legal terminology. If a legal team misses an obvious English trace of ChatGPT on the face of a document, it has no credible basis for assuring a judge that the underlying foreign-language evidence has been reliably verified.

Professional Misconduct Findings Based on Unverified ChatGPT Translations: VA v JL [2025]

Even more concerning for legal practitioners is the New Zealand disciplinary decision in VA v JL [2025] NZLCRO 123, which arose from a client’s complaint regarding her lawyer’s handling of an employment and commercial dispute.

A central issue before the Legal Complaints Review Officer was whether the lawyer had misled her client by advising that commencing High Court proceedings could be used to halt or disrupt proceedings before the Employment Relations Authority. Crucially, the disputed advice was contained in chat messages exchanged between the lawyer and the client on 23 July 2021 in a foreign language (anonymised in the decision as “Language F”).

The client submitted a fuller record of the foreign-language chat exchange accompanied by English translations that the client stated she had generated using ChatGPT. In the ChatGPT-translated version, the lawyer was recorded as stating: “Yes, it will work” and “It does work! This is feasible!” The lawyer denied sending the disputed message and provided a shorter record with her own translations.

In making findings of unsatisfactory conduct against the lawyer, the Review Officer preferred the completeness of the client’s documentary record at paragraph [112] and expressly relied at paragraphs [208] and [209] on the statements “Yes, it will work” and “It does work! This is feasible!” when assessing the legal advice the lawyer had given. Yet nowhere in the published decision did the Review Officer explain how he established that the client’s ChatGPT translation accurately reflected the nuances of what had been written in Language F.

In legal advice concerning litigation strategy, the boundary between telling a client that a procedural route is theoretically possible and assuring the client that it will succeed turns on fine linguistic distinctions of modality and qualification. VA v JL serves as a stark warning to practising lawyers on two fronts. First, any foreign-language message you send to a client may subsequently be run through ChatGPT by that client and placed before a disciplinary tribunal as evidence of professional misconduct. Secondly, decision-makers who cannot read the source language may conflate the authenticity of a foreign-language record with the accuracy of its fluent English AI translation, treating unverified chatbot phrasing as proof of what a lawyer advised.

Confidentiality Breaches and the Vacuum of Vendor Liability

Beyond evidentiary and disciplinary perils in court, lawyers who upload client contracts, corporate disclosures, or pleadings into public machine translation or generative AI platforms face direct regulatory and contractual exposure. As Argyri Panezi and I examined in our paper for the International Conference on Machine Learning (Workshop on Generative AI and Law, ICML, 2023) and as the High Court of England and Wales emphasised in Ayinde v London Borough of Haringey [2025] EWHC 1383 regarding lawyers’ non-delegable supervisory duties over AI, practitioners remain bound by strict statutory duties of professional secrecy, UK and EU General Data Protection Regulation (GDPR) obligations, and contractual Non-Disclosure Agreements (NDAs).

When an unverified AI translation causes financial loss or misses a statutory condition, the terms of service of every commercial AI and machine translation provider disclaim all warranties of accuracy and fitness for purpose. As I explored at the joint EULITA and PEEMPIP conference in Athens (Is Anyone Liable for Legal Translation?, 2024), technology vendors accept zero liability for the legal consequences of their outputs. The entire burden of professional negligence, regulatory sanction, and financial loss falls upon the instructing lawyer or corporate user who chose to rely on the machine.

6. Frequently Asked Questions

Has modern generative AI solved the legal translation errors seen in earlier tools like Google Translate?

No. While neural machine translation and generative AI models produce much smoother English sentences than statistical machine translation did ten years ago, empirical research shows that high fluency masks severe accuracy and terminological errors. Recent court decisions such as Lozano González v Roberge (where ChatGPT rewrote statutory provisions) and Euroboor BV v Grafova (where a US court struggled to understand a Google Translate rendering of a Dutch judgment) confirm that modern AI tools still fail to preserve legal meaning in contentious and transactional settings.

What are the risks to a lawyer who submits or relies on an AI-translated document in legal proceedings?

A lawyer who relies on or files an unverified AI translation risks judicial criticism for failing to check document provenance (as seen in AA v Secretary of State for the Home Department [2026] UKFTT PA747122024), file-level terminology drift across related contractual and litigation documents (as highlighted in Hellenic Supreme Court Judgment No. 221/2026), breaches of client confidentiality and GDPR obligations when uploading sensitive material to third-party servers, and full professional liability for any resulting loss. Furthermore, as VA v JL [2025] NZLCRO 123 illustrates, lawyers also face disciplinary risk when unverified ChatGPT translations of client communications are relied upon in professional conduct proceedings.

Is having a bilingual colleague or family member check a ChatGPT translation sufficient for legal purposes?

No. Reviewing an AI-generated translation against a foreign-language original requires specialist competence in both comparative law and legal translation. Empirical studies of machine translation post-editing (Sosoni, O’Shea & Stasimioti, 2022) demonstrate that the polished surface fluency of neural outputs anchors human reviewers, causing them to miss critical system-bound legal errors, omitted qualifications, and false equivalences between civil law and common law terminology.

7. Protecting Both Client and Counsel Through Specialist Lawyer-Linguist Expertise

The lesson of the past decade from KIP UK Ltd and Essential Telecom in 2016 to Hellenic Supreme Court Judgment No. 221/2026, AA v SSHD, and VA v JL in 2025 and 2026 is unmistakable: legal translation shapes the operative force of contracts, the admissibility of evidence, and the professional standing of legal advisers. Treating it as a zero-consequence mechanical task to be delegated to a probabilistic chatbot exposes both client and counsel to avoidable legal hazard.

Founded in 1997 in London and led by lawyer-linguist John O’Shea (LL.B. (Hons), LL.M.), JurTrans has spent nearly three decades providing specialist Greek-to-English and English-to-Greek legal and financial translation for international law firms, corporate legal departments, financial institutions, and private clients. Our practice is grounded in formal legal training, nearly thirty years of hands-on transactional and litigation experience across Greece, Cyprus, and the United Kingdom, and authoritative legal scholarship, including co-translating Greece’s foundational statutory codes (The Greek Penal Code, The Greek Code of Civil Procedure, The Greek Code of Criminal Procedure, and the Greek Code of Private Maritime Law) within the Lex Graeca series.

When you instruct JurTrans on a commercial contract, corporate finance transaction, regulatory filing, or cross-border litigation bundle, we protect both client and instructing counsel by ensuring:

• From-Scratch Specialist Translation: Every document is translated from scratch by a qualified specialist without reliance on public machine translation or generative AI, eliminating the risk of algorithmic hallucinations and common law terminology bias.

• File-Level Terminological Consistency: In multi-year commercial relationships and contentious proceedings, we cross-check new notices, pleadings, and exhibits against the terminology already established in your underlying agreements and court file.

• Source-Text Detective Work: During 2024, across 946 Greek legal documents translated into English at JurTrans, we identified source-text errors, ambiguous statutory citations, or internal inconsistencies in approximately 95% of the originals. Rather than silently guessing or flattening an ambiguity, we preserve the integrity of the text and flag source-text defects directly for instructing counsel.

• Strict Confidentiality and Accountability: All documents are handled under strict professional confidentiality and formal Non-Disclosure Agreements, backed by professional accountability that no AI vendor provides.

To discuss a Greek or Cypriot legal or financial translation requirement in complete confidence, contact John O’Shea at JurTrans via jurtrans.com or email info@jurtrans.com.