Simplifying Administrative Language with AI Without Losing Legal Certainty

Why it's worth simplifying administrative texts with AI

Citizens abandon procedures because of unclear instructions. Simplifying language reduces inquiries, mistakes in applications and administrative appeals. AI enables automating summaries, step-by-step instructions and FAQs, but done poorly it can introduce legal inconsistencies, violate the GDPR or fail to meet transparency obligations under the EU AI Act.

This document provides an operational approach to automate that simplification without sacrificing legal certainty or traceability.

Principles that should guide the project

• Preserve legal equivalence: the simplified version must reflect the obligations, deadlines and effects of the original text.
• Human oversight (human-in-the-loop): legal professionals and procedure owners review and validate the texts.
• Traceability and record keeping: retain originals, simplified versions, prompt/model/version and validation decisions.
• Regulatory compliance: GDPR (data protection in examples and templates), ENS if it contains sensitive information, and transparency requirements of the EU AI Act applicable to generative systems.
• Accessibility and inclusion: ensure plain language and alternative formats.

Recommended operational workflow (pipeline)

1. Ingestion and classification

   • Identify document type: decree, ordinance, form or notification.
   • Tag critical metadata: file number, department, publication date, legal effects.

2. Preprocessing

   • Remove personal data or convert real examples into anonymized/synthetic data in accordance with the GDPR.
   • Detect sections with normative content (articles, requirements, sanctions) for conservative handling.

3. Assisted generation

   • Templates defined by area: executive summary, step-by-step instructions, citizen checklist, frequently asked questions.
   • Use models with output controls (e.g., structured prompts, safety filters) and lock model versions during validation.

4. Legal and functional validation

   • Legal verification checklist (see below).
   • Dual review: the area’s lawyer + the procedure owner.
   • Digital signature or recorded approval before publication.

5. Publication and feedback

   • Publish alongside the original text with a clear notice: “Informative summary — does not replace the legal text.”
   • Citizen feedback channel to detect ambiguities or errors.

6. Monitoring and traceability

   • Record model/version, prompt, approving user and timestamp.
   • Regular audits and regression tests after regulatory changes or model updates.

Practical checklist for legal validation

Before publishing a simplified version, confirm:

• Are the substantive requirements preserved (deadlines, conditions, obligated parties)?
• Does the simplification introduce any new obligations or remove exceptions?
• Have examples containing personal data been identified and anonymized?
• Does the summary include a notice that it is informative and a reference to the original legal text?
• Are the model, the template and the person who validated it recorded?
• Has accessibility been checked (plain language, contrast, screen reader compatibility)?

Concrete use cases and limits

• Useful: summaries of decrees, instructions for submitting applications, FAQs for recurring procedures, automatic confirmation messages.
• Not recommended without strict control: automatic rewriting of court rulings, complex contractual texts or binding legal interpretations.

Technical and contractual considerations

• Require in contracts with vendors:
  • Versioning of models and access to generation logs.
  • SLAs for rapid rollback and correction when errors are detected.
  • Obligation to provide portability of prompts and prompt logs for audit purposes.
• Maintain test environments with synthetic data to validate changes before production.
• Configure access control and encryption in accordance with the ENS (Royal Decree 311/2022) if documents contain sensitive data.

Quality control metrics

• Rejection rate in legal validation (target: low and decreasing).
• Average time for legal approval per document.
• Reduction in citizen inquiries about the procedure.
• Errors detected post-publication and time to correct them.

Example minimal template for a decree summary

• Title of the act and date.
• Purpose in 2–3 sentences.
• Who it affects (recipients).
• Key deadlines (cut-off dates).
• Essential requirements (documents/conditions).
• Summarised procedure (3–6 steps).
• Consequences of non-compliance.
• Link to the full legal text and contact details.

Practical integration into the organization

• Pilot: choose 3 high-volume, low-risk procedures for a 60–90 day pilot.
• Roles: technical team (automation), legal unit (validation), citizen services area (feedback).
• Tools: template repository, version manager and approval register (ideally integrated into your document management platform).

A modular digital government platform can integrate this pipeline with governance and traceability controls already used by the administration, maintaining compliance and operational efficiency.

Call to action (takeaway)

Immediate actions in 30 days:

1. Select 3 candidate procedures (high volume, low impact).
2. Define minimal summary templates and the legal checklist.
3. Prepare a test environment with anonymized documents.
4. Run a 60-day pilot with legal validation at each iteration.
5. Record metrics and plan scaling if validation demonstrates preservation of legal equivalence.

AI-driven simplification improves citizen service if designed with legal controls and traceability from the start.