ASD ISM 2084Document AI Model and System Characteristics
Official control statement
AI-specific documentation, including AI model cards and AI system cards (or equivalent artefacts), is used to document AI model characteristics, system architectures, use cases and security risks.
Quoted as published. Everything else on this page is written by Control Stack.
In plain English
Create detailed documents about AI models and systems, including their architecture and security risks.
What this means in practice
This control is about writing down important details about our AI systems, like how they work and the risks they might have. It's important because without this documentation, we could make expensive mistakes or face security issues with our AI models.
Framework
ASD Information Security Manual (ISM)
Control effect (Control Stack)
Proactive
Classifications
NC, OS, P, S, TS
ISM last updated
June 2026
Control Stack last updated
29 Sept 2026
E8 maturity levels
N/A
Guideline
Guidelines for software developmentTopic
Secure artificial intelligence application development
Why it matters
Without documenting AI model details and risks, businesses may experience security breaches, financial loss, or reputational damage.
Operational notes
Regularly update AI documentation to reflect system changes and new risks. Ensure all team members can access and understand these documents.
Implementation tips
- System owners should create and maintain AI model cards. To do this, describe the AI model's purpose, how it operates, what data it uses, and potential risks, making sure everything is clear and easy to understand.
- The IT team should document the system architecture. Write down details about how the AI system is set up, including hardware, software, and network components, so everyone knows how the system functions.
- Managers need to review AI system cards with their teams. Schedule regular meetings to discuss these documents, ensuring all team members understand potential security and privacy risks associated with the AI models.
- HR should organise training for staff on AI security risks. Set up workshops to educate employees on recognising and handling any security threats or ethical issues related to AI.
- Procurement should ensure AI systems selected align with documented use cases and security needs. Collaborate with the IT team to evaluate vendors' AI systems against the documented requirements and risks.
Audit / evidence tips
- AskAsk for the AI model cards (or equivalent artefacts) for each AI model in use.Look atLook at how well each card explains the model's purpose, how it operates, the data it uses and its known security risks.GoodGood model cards are detailed, easy to read and updated regularly so they reflect the model as currently deployed.
- AskRequest the AI system cards or system architecture documentation for each AI system.Look atCheck that the documentation covers all relevant hardware, software and network components, along with the system's intended use cases.GoodA complete document accurately reflects the current system setup rather than an outdated or planned design.
- AskAsk for records of team review meetings where AI system cards were discussed.Look atLook for meeting notes or minutes that show the cards were reviewed and their content understood by the relevant people.GoodGood notes capture the key points discussed and highlight any action items raised, such as updates needed to the documentation.
- AskRequest training attendance records and training materials covering AI risks.Look atCheck that the staff responsible for AI models and systems have been trained on AI security risks and that the materials cover the risks recorded in the model and system cards.GoodQuality training uses practical examples and scenarios, and attendance records show the relevant staff completed it.
- AskAsk for the procurement criteria and evaluation reports used when selecting or assessing AI systems.Look atExamine whether the criteria and reports align with the use cases and security risks documented in the model and system cards.GoodGood practice shows a thorough evaluation process that was documented and followed, with findings consistent with the AI documentation.
Cross-framework mappings
How ISM-2084 relates to controls across ISO/IEC 27001, ISO/IEC 42001, Essential Eight, and ASD ISM.
ISO 27001
| Control | Notes | Details |
|---|---|---|
layersPartially meets(1)expand_less | ||
| Annex A 5.8 | Annex A 5.8 requires information security to be integrated into project management so project delivery considers security risks and controls | |
sync_altPartially overlaps(1)expand_less | ||
| Annex A 8.27 | ISM-2084 requires AI-specific documentation (e.g | |
ISO 42001
| Control | Notes | Details |
|---|---|---|
sync_altPartially overlaps(2)expand_less | ||
| Annex A 6.2.7 | Annex A 6.2.7 requires the organisation to determine what AI system technical documentation is needed for each category of interested par... | |
| Annex A 8.2 | ISO/IEC 42001 Annex A 8.2 requires the organisation to determine and provide the information that users of an AI system need | |
handshakeSupports(1)expand_less | ||
| Annex A 9.4 | Annex A 9.4 requires the organisation to ensure an AI system is used only for its documented intended uses and within documented limits | |
These mappings show relationships between controls across frameworks. They do not imply full equivalence or certification.
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See all Guidelines for software development controls, or browse the full ASD ISM library.