AI translation moves fast — but legal and infosec teams keep flagging the question: what happens to confidential content when it goes into an AI translator? This post lays out the security risks, the checklist for vendor selection, and the contract clauses worth requiring. Aimed at legal, infosec, procurement, and anyone whose signature unlocks an enterprise translation tool.
Five security risks in AI translation
1. Input used for model training
Free / consumer AI translation tools commonly state that input data may be used to improve services or train models. The contract you translated this morning could plausibly surface in another user's output later.
Business APIs and paid plans typically say "not used for training" — but verify the terms. If it's not written, don't use it.
2. Transport encryption
Baseline: HTTPS (TLS 1.2+). Without it, public Wi-Fi exposes your data to man-in-the-middle attacks. Enterprise usage usually requires VPN + HTTPS minimum.
3. Storage location and retention
- Geography: Japan, US, EU, other?
- Retention: immediate purge, 24h, 30 days, 90 days, indefinite?
- Deletion mode: logical (flag only) or physical (gone from storage)?
- Backups: how long until backups also expire?
For GDPR (EU personal data), in-region storage may be mandatory.
4. Access control and audit logs
- SSO support (SAML, OAuth, OIDC)
- Role-based access (admin / user / guest)
- Audit log of who translated what
- Process for deactivating departed employees
5. Third-party data transfer
The translation vendor's backend likely calls an LLM provider (Anthropic, OpenAI, Google). Confirm:
- Which LLM provider receives the data
- Provider's data-handling terms
- Whether providers cross-share
Five vendor-selection checks
1. Third-party certifications
- SOC 2 Type II — broadly used by US SaaS, demonstrates ongoing operational controls
- ISO/IEC 27001 — international infosec management standard
- ISMS — Japan's equivalent
- GDPR conformity — for any EU personal data
2. Data Processing Agreement (DPA)
Standard for any enterprise contract. A good DPA covers:
- Types of data processed and purpose
- Storage location and retention
- List of subprocessors (third parties used downstream)
- Breach notification timeline (typically 24–72 hours)
- Data deletion obligations on contract termination
3. NDA willingness
For high-confidentiality docs, ability to sign a separate NDA with the vendor is a meaningful signal. Many SaaS terms include confidentiality language already, but a standalone NDA is the safer ground.
4. VPC / on-prem deployment options
For the highest sensitivity (government, defense, clinical research):
- VPC deployment — runs inside your cloud account
- On-premises — runs in your data center
- Dedicated tenant — no shared infrastructure
Most companies don't need this, but availability of these options signals the vendor is wired for enterprise.
5. Incident response process
- Detection-to-notification time target
- Scope-of-impact analysis methodology
- Post-incident remediation plan
Industry-specific extras
- Finance: FISC safety standards, capital regs. Translations of customer-data documents need stricter controls.
- Healthcare: APPI, medical-info safety guidelines. Anonymize patient data before translation.
- Government / public sector: ISMAP registration is increasingly required for SaaS used inside Japanese public-sector procurement.
- Export control: translating technical docs may intersect with foreign-exchange / export-control regs.
How BizHonyaku handles security
- Input is not used for model training
- HTTPS (TLS 1.3) in transit
- Translation history auto-deleted after 90 days (configurable on enterprise plans)
- Logs stored separately for audit
- Backend: Anthropic Claude (business API). Anthropic contractually does not use input for model training.
- SSO support on enterprise plans
- DPA and NDA available
Operational rules to set internally
- Document classification: what may go through AI translation, what may not
- Anonymize personal / payment data before submitting
- Review usage periodically (who is translating what)
- Deactivate accounts and revoke history access for departed staff
Summary
AI translation of confidential content is a convenience-vs-risk trade-off that the right vendor and the right operational rules can shrink to near zero. The non-negotiables: (1) input is not used for training, (2) third-party certifications exist, (3) DPA and NDA are signable, (4) audit logs are real, (5) internal usage rules are written down.
BizHonyaku covers all five through its enterprise plan. Reach out via the contact form for a security-requirements walkthrough.