# A.4.3 Data resources

Within resource identification, document information about the data resources the AI system uses. In practice the record is data resource records covering provenance, last update date, ML data categories, labelling process, intended use, quality, retention and disposal, known bias and preparation. For data resources the evidence is an inventory, not a statement.

- Framework: ISO/IEC 42001:2023
- Cited to: ISO/IEC 42001:2023, Annex A control A.4.3
- Source: https://www.iso.org/standard/81230.html
- Last updated: 2026-10-20

## What it asks

Within resource identification, document information about the data resources the AI system uses.

## Where generative AI changes the answer

Data resources for a generative system include the retrieval corpus and the prompt history, which are often owned by nobody and retained by default.

## Who it binds

The AI system owner and the functions that supply data, tooling, computing and people.

## Evidence an auditor samples

- Data resource records covering provenance, last update date, ML data categories, labelling process, intended use, quality, retention and disposal, known bias and preparation

## The test you can run

Ask for the data and tooling inventory for the use, and check that the evaluation set is in it.

## Common failures

- Known bias in datasets undocumented
- No record of when data were last updated

## Before the draft publishes

List the data, tooling, computing and people the use depends on, and mark which of them the organisation does not control.

## What this page does not say

It does not state the text of ISO/IEC DTS 25568, because ISO has not published the draft's clause text. It does not certify anything.

Not legal advice; does not certify.