Map Your AI Risk Landscape
Aligned with ISO/IEC 23894

An ISO/IEC 23894 AI Risk Assessment is a structured, independent evaluation of how an organization identifies, analyzes, evaluates, and treats risks associated with its artificial intelligence systems. ISO/IEC 23894 provides specific guidance on AI risk management and complements management system standards such as ISO/IEC 42001 and general risk management frameworks such as ISO 31000. The assessment analyzes technical, operational, legal, ethical, and organizational risks throughout the AI lifecycle, including data risks, model risks, deployment risks, and downstream effects. The result is a documented risk profile, a control gap analysis, and a prioritized mitigation roadmap aligned with international AI risk management principles.

Any organization that develops, deploys, or uses AI systems and needs a formal assessment of the associated risks. This includes organizations operating in regulated sectors such as financial services, healthcare, insurance, or critical infrastructure, organizations that need to demonstrate AI risk governance to regulators, investors, or clients, and companies preparing to implement an AI management system under ISO/IEC 42001 that need a prior risk diagnostic.

No. ISO/IEC 23894 is a guidance standard, not a requirements standard. There is no ISO/IEC 23894 certification issued by certification bodies. Its value lies in providing a structured, internationally recognized framework for evaluating and managing AI risks, the results of which can directly feed into a certifiable AI management system under ISO/IEC 42001.

ISO 31000 is the general risk management standard, applicable to any type of risk in any sector. ISO/IEC 23894 applies ISO 31000 principles specifically to the context of artificial intelligence, adding guidance on AI-specific risks such as algorithmic bias, lack of explainability, failures in human oversight, training data quality, and unintended effects in deployment. Organizations already using ISO 31000 will find ISO/IEC 23894 a natural extension for their AI systems.

The standard timeline is approximately four weeks, depending on the scope, the number of AI systems assessed, and the operational complexity of the organization. Organizations with multiple AI systems or with AI processes embedded in critical operations may require a longer timeline.

The assessment requires access to internal AI governance policies, an inventory of AI systems, technical documentation for the models, existing risk registers, human oversight procedures, post-deployment monitoring mechanisms, and any prior impact assessments or audits conducted on the AI systems.

A structured report that includes a comprehensive risk profile of the AI systems assessed, a gap analysis between existing controls and ISO/IEC 23894 guidance, a risk prioritization matrix classified by likelihood and impact, and a mitigation roadmap with prioritized corrective actions and recommended timelines. The report is an auditable document that can be presented to regulators, investors, or procurement teams.

ISO/IEC 23894 and ISO/IEC 42001 are complementary. ISO/IEC 23894 provides the guidance for identifying and evaluating AI risks. ISO/IEC 42001 provides the management system framework for addressing those risks in a structured and certifiable manner. Organizations that first carry out a risk assessment under ISO/IEC 23894 can use the results as a foundation to build or strengthen the risk management dimension within their AI management system under ISO/IEC 42001, facilitating future certification. Zertia offers both services and can design an integrated engagement.

All three frameworks address AI risk management from complementary perspectives. ISO/IEC 23894 provides technical guidance on AI risk identification and treatment. The NIST AI RMF provides an operational risk governance framework. The EU AI Act establishes legal risk management obligations for high-risk systems. An assessment under ISO/IEC 23894 generates results that can be mapped directly to the requirements of both frameworks, providing a solid technical foundation for both regulatory defensibility and certification.

Yes. The resulting report provides documented evidence of structured AI risk management aligned with an internationally recognized standard. This can facilitate procurement processes with large enterprises that require risk governance from their suppliers, investor due diligence processes evaluating technological risk exposure, and public tenders where conformity with international risk management frameworks is valued.