Skip to content
AI Policy Generator

Training or fine-tuning models on own data

Training, fine-tuning or grounding models on customer, employee or public data. It requires a legal basis to reuse personal data, dataset documentation and, when developing a general-purpose model, provider duties.

Examples

By country

We only list countries where an obligation in force or adopted mentions this use case.

How rules treat it, by jurisdiction

JurisdictionLevelDateNote
European UnionData protection—GDPR and EDPB Opinion 28/2024: models are not presumed anonymous and legitimate interest needs a documented test; developing a general-purpose model triggers technical documentation, copyright policy and training-data summary duties since Aug 2, 2025.
EcuadorData protectionMarch 10, 2026SPDP general rule on AI and the legitimate interest resolution (2025).
MexicoData protectionMarch 21, 20252025 data protection law: new consent for different purposes, such as training.
PeruData protectionMarch 31, 2025Law 29733 and its regulation (DS 016-2024-JUS): purpose, consent and cross-border flows.
ChileData protectionDecember 1, 2026Law 21,719: legal bases and purpose compatibility.
ColombiaData protection—Law 1581/2012: prior authorization and informed purpose.
ArgentinaData protection—Law 25,326: purpose and consent.
BrazilData protection—LGPD; the ANPD prioritizes AI in 2026-2027.
CaliforniaTransparencyJanuary 1, 2026AB 2013: generative AI developers must publish information about training data.

Common base documents

Depending on your situation

If sensitive or children's data is used
If data is processed abroad
If the model goes into production
If a general-purpose model is developed

Related kits

Includes 7 documents

Self-Hosted and Open-Weight Models Kit

Seven base documents for hosting in-house or open-weight models: provenance, security baseline, adversarial testing, architecture, model card, life cycle and rollback.

USD 149USD 233

Complete kit · available to buy

Find out what applies to you (free)