ISO 42001 AI management systems
Cube Cyber helps Australian organisations build and certify ISO 42001 AI management systems, the international standard for governing how AI is developed, procured and used. From AI policy and impact assessment through to implementation and certification audit, we make AI use visible, controlled and defensible, integrated with your existing ISO 27001 system rather than duplicating it. Our practitioners hold ISO 42001 Lead Auditor certification.
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ISO 42001 conversations start from three realities:
Early certification is a differentiator; late certification is a scramble. The organisations moving now are those whose customers are beginning to ask, those in regulated sectors where AI scrutiny is clearly coming, and technology companies who watched ISO 27001 become a procurement gate and recognise the pattern repeating. There is also a practical window: while your AI footprint is still relatively small, building the management system is far cheaper than retrofitting governance across a hundred embedded uses later.
Core capabilities & deliverables
AI governance readiness assessment
Establish current AI use across the organisation, including the shadow inventory nobody commissioned, and assess it against ISO 42001 requirements, producing a sequenced path to certification.
AI management system design and build
The AIMS itself: AI policy, roles and accountabilities, risk and impact assessment processes, lifecycle controls for AI systems, and supplier requirements for AI-enabled services, built around your actual AI use rather than a hypothetical one.
AI risk and impact assessment
Structured assessment of AI systems for the risks that matter, data leakage, bias and fairness, explainability, misuse and third-party dependency, in your regulatory and commercial context, feeding treatment decisions with named owners.
Integration with your ISMS
ISO 42001 follows the same management-system structure as ISO 27001. We integrate the two, one risk method, one audit rhythm, one management review, so AI governance strengthens the existing system instead of competing with it.
Control implementation support
Technical and process controls behind the policy, approved tooling, data protection for AI workloads, monitoring of AI use, drawing on our AI Security practice, so the management system governs reality.
Internal audit and certification support
Lead Auditor certified internal audit, management review facilitation and support through the certification audit, the same disciplines we apply to ISO 27001, applied to the newer standard.
AIMS programs follow the same four-stage path as our ISO 27001 work:
Assess
AI use discovery and gap assessment against ISO 42001, with scope set around the AI that actually carries risk.
Build
AIMS development, policy, impact assessment, lifecycle controls and supplier requirements, integrated with the existing ISMS where one exists.
Operate and evidence
The system runs, impact assessments happen on real AI decisions, and evidence accumulates the way auditors need to see it.
Certify and maintain
Certification audit support, then the maintenance rhythm, with the AI landscape moving fast enough that the review cycle genuinely earns its keep.
Work aligns to ISO/IEC 42001, integrates with ISO/IEC 27001, and draws on the NIST AI Risk Management Framework and Australian Privacy Act obligations. Where clients want governance without immediate certification, the same system can operate as an internal framework with certification as a later step.
ISO/IEC 42001ISO/IEC 27001NIST Framework
APA ObligationsFrequently asked questions
ISO/IEC 42001 is the international standard for AI management systems, the governance structure for how an organisation develops, procures and uses AI responsibly. It covers policy, risk and impact assessment, lifecycle controls and accountability, and it is certifiable, meaning an accredited body can audit your system and issue a certificate customers can verify.
The standard covers use, not just development, and for most Australian organisations, use is where the risk lives: staff pasting data into public tools, AI features inside SaaS platforms, and AI-enabled suppliers. If AI outputs influence decisions about people, money or safety, governance is warranted, and certification is how you demonstrate it externally.
Materially less than starting from nothing. The management-system machinery, risk method, document control, internal audit, management review, extends rather than duplicates, and we run the two as one integrated system. The genuinely new work is the AI-specific layer: use discovery, impact assessment and lifecycle controls.
Comparable to ISO 27001 for a similar scope: several months to a year depending on the size of your AI footprint and whether an ISMS already exists to build on. Organisations with mature ISO 27001 systems and a modest AI estate sit at the shorter end.
Adoption is early but moving in exactly the pattern ISO 27001 followed: technology vendors certifying to differentiate, then enterprise procurement adding it to questionnaires, then regulated sectors treating it as expected. Certifying while it is a differentiator costs the same as certifying later under deadline pressure, and returns more.
Yes. The same discovery, policy, impact assessment and control work operates perfectly well as an internal governance framework, and several clients run it that way with certification held as a later option. Building it to the standard from the start means that option stays cheap.
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