ISO/IEC 23894 Toolkit – Artificial Intelligence Risk Management

The toolkit is designed for organizations that develop, provide, deploy, integrate, procure, or use AI systems, including AI governance teams, risk managers, model risk teams, data scientists, ML engineers, privacy and security professionals, compliance teams, internal auditors, and consultants.

It includes editable Word policies, procedures, plans and reports; Excel registers, matrices, checklists, trackers and dashboards; and PowerPoint review presentations covering AI governance, context, risk criteria, lifecycle risk, data, model, fairness, privacy, security, transparency, human oversight, treatment, validation, monitoring, incidents, and management review.

The supplied implementation register is organized into 20 implementation parts containing 147 templates. It progresses from enterprise AI risk governance and scope through lifecycle risk identification, analysis, evaluation, treatment, monitoring, reporting, and system closeout.

Yes. The page provides a detailed document index so you can review the included file names and file types before purchase. The standard Index File and Payment Guide section from the template page is retained.

Yes. It includes enterprise AI risk policy, implementation charter, governance RACI, readiness assessment, scope and applicability, integration and tailoring, gap assessment, organizational context, interested parties, objectives, legal and contractual obligations, and implementation priorities.

Yes. It includes AI risk assessment methodology, appetite and tolerance criteria, escalation and decision procedures, impact and likelihood scoring, acceptance thresholds, risk categories, review triggers, and assessment frequencies.

Yes. It includes intended use and operating context profiles, lifecycle risk ownership plans, enterprise AI system inventories, risk tiering, excluded use matrices, architecture and data flow dependencies, lifecycle stages, owners, and control responsibilities.

Yes. It includes AI risk communication and consultation plans, stakeholder and affected party analysis, expectations and potential harms registers, feedback and grievance procedures, consultation logs, risk concerns, escalation, and response tracking.

Yes. It includes risk identification procedures, scenario and harm descriptions, threat and risk source registers, failure modes, foreseeable misuse, objectives to risk traceability, cause and consequence analysis, and workshop actions.

Yes. It includes data risk and provenance procedures, training, validation and production data assessment, dataset inventories, data lineage, quality, representativeness, integrity, consent, usage rights, restrictions, drift, contamination, and leakage risks.

Yes. It includes model risk analysis, assumptions, operating limits, failure modes, performance risks, validation confidence, uncertainty, out of distribution and edge cases, robustness, stress testing, and adversarial testing.

Yes. It includes fairness and bias risk assessment, human and societal impact assessment, affected group and disparate impact matrices, bias source and mitigation tracking, fairness metrics, test results, and stakeholder harm registers.

Payment is processed securely through PayPal. Depending on availability in your country, payment may be made using a PayPal account or supported major credit and debit cards.

After payment is completed, the toolkit is provided through the site's download process. We recommend downloading the archive promptly and retaining a secure backup together with the purchase confirmation.

Yes. It includes privacy, security and misuse risk assessment, adversarial abuse scenarios, sensitive data risk, API and model security, prompt injection and data leakage, explainability needs and limitations, human oversight, intervention, override responsibilities, automation bias, disclosure, and transparency controls.

Yes. It includes inherent and residual risk analysis, existing control effectiveness, uncertainty and confidence, evaluation and prioritization, risk acceptance and exception approval, management escalation, treatment planning, control selection, action ownership, control implementation evidence, and reassessment.

Yes. It includes risk based verification and validation, risk to test traceability, edge case and acceptance criteria, adversarial robustness and safety testing, defect closure, release risk gates, third party AI due diligence, supplier assurance agreements, provider registers, dependency risk, and corrective actions.

Yes. It includes deployment readiness and rollback, model and data change risk, go live approval, version baselines, material change reassessment, continuous risk monitoring, data and model drift, incidents and near misses, fallback procedures, root cause and corrective action, management review, independent review, retirement, data disposal, and lessons learned.

Check that the archive has downloaded completely and that your extraction software supports the file format. If the issue continues, contact support with your purchase reference, the affected file name, and a screenshot or description of the error.