# B.6 System hardware issues

AI-related risk source: Faults, limits and tampering in the hardware running or feeding the AI system, including sensors and accelerators, can corrupt data and computation and so its behaviour. The artefact behind the answer is hardware fault and dependency analysis for AI platforms. Use system hardware issues as a prompt in the identification step, not as a finding.

- Framework: ISO/IEC 23894:2023
- Cited to: ISO/IEC 23894:2023, clause B.6
- Source: https://www.iso.org/standard/77304.html
- Last updated: 2026-10-20

## What it asks

AI-related risk source: Faults, limits and tampering in the hardware running or feeding the AI system, including sensors and accelerators, can corrupt data and computation and so its behaviour.

## Where generative AI changes the answer

Hardware and capacity issues surface as degraded or truncated outputs, which users read as a wrong answer rather than a system fault.

## Who it binds

The assessment team that runs identification, and the business owner who knows the use.

## Evidence an auditor samples

- Hardware fault and dependency analysis for AI platforms

## The test you can run

Ask the assessment team to name the risk sources they considered. Compare the list with the ones present in the use.

## Common failures

- Hardware assumed reliable and secure

## Before the draft publishes

Add the sources that apply to your use to the identification checklist, with a short note on why each one is or is not present.

## 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.