Training-data diligence should examine acquisition, permitted use, personal-data processing and relevant intellectual-property rights. Distinguish pretraining, fine-tuning, retrieval and customer-input reuse. A licence to access material does not necessarily permit model training, and an indemnity does not establish that the underlying use is lawful.
The business situation
A vendor says its model was trained on publicly available material. The buyer assumes that means the data can be used without restriction. The statement does not reveal licensing conditions, personal-data sources or what the vendor knows about upstream datasets.
AI governance starts with a use case and a responsible legal entity. A model is not itself a Data Fiduciary. The organisation determining the purpose and means of personal-data processing may be one. Contract, intellectual-property, consumer, employment and sector rules can apply alongside data-protection law; the relevant obligations depend on the deployment.
What needs examining
01. Ask questions the supplier can actually answer
Request dataset categories, acquisition methods, licensing approach and known restrictions, rather than demanding a list the vendor cannot meaningfully produce. Distinguish verified provenance from supplier assumptions and unavailable records. The diligence note should show the limits of assurance; a complete-looking questionnaire can otherwise disguise a significant information gap.
02. Keep privacy and copyright analyses separate
Material may be accessible online while still subject to copyright, confidentiality, database terms or personal-data requirements. Evaluate the applicable law and contemplated use. The DPDP public-availability exclusion is not a general licence to scrape anything visible on the internet. Similarly, obtaining personal-data consent does not automatically clear intellectual-property rights.
03. Negotiate around the residual risk
Define warranties the supplier can support, excluded uses, cooperation in claims and the scope of any indemnity. Consider whether the business will publish outputs, use them internally or embed them in another product. Check defence control, replacement rights and the consequences of disabling a model. Allocate residual risk explicitly where the provenance record remains incomplete.
Law, contract and recommended practice
Applicable Indian statutes and sector directions are mandatory where their scope is met. NIST AI RMF is a voluntary governance framework, unless particular commitments become binding through a contract or another applicable requirement. Its GOVERN, MAP, MEASURE and MANAGE functions can organise evidence without creating a new Indian legal obligation.
Connect the control to the evidence
Use this table to scope the review. The legal basis and the practical control are identified separately.
| Obligation or objective | Practical control | Evidence to retain |
|---|---|---|
| Law, where applicable Establish rights and lawful processing | Separate IP and personal-data assessments | Source licences and legal analysis |
| Contractual control Align assurance with vendor knowledge | Specific warranties and claim cooperation | Disclosure schedule and negotiated terms |
| Recommended practice Preserve the limits of diligence | Record unknowns and permitted use restrictions | Approval note and residual-risk register |
Records to prepare
Bring the complete, current record to the review. Preserve earlier versions where a change or disputed event makes them relevant.
Common questions
Does public availability make training automatically lawful?
No. Public visibility, copyright permissions and personal-data treatment are different questions. The applicable rules and facts must be assessed separately, including how the material became publicly available.
Can an indemnity replace provenance diligence?
No. It may allocate part of the financial exposure, subject to scope and enforceability, but it does not prove permission or prevent service disruption. Consider the supplier's ability to respond as well as the wording.
Make the approval file say what is known, what remains unknown and which uses are permitted. That is more useful than an unqualified compliant label.
Legislation & official resources
These references identify the governing frameworks. Confirm the current text, relevant amendments and applicable judicial position for the matter.
- NIST AI Risk Management FrameworkNational Institute of Standards and Technology · Voluntary governance framework. It does not, by itself, create an Indian statutory duty.
- Indian Contract Act, 1872Government of Uttar Pradesh · Commercial Tax Department · Government-hosted statutory reference. Read with applicable amendments, special law and judicial interpretation.
- Digital Personal Data Protection frameworkMinistry of Electronics and Information Technology · Official framework resource. Apply the relevant Act, Rules and commencement notifications together.
This note is general information. The scenario is hypothetical and does not describe a client matter. The legal result depends on the facts, documents, jurisdiction and operative law. No individual lawyer review is represented by the preparation date.
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