⚡ Quick Summary
The OWASP AI Maturity Assessment (AIMA) is an open, community-driven framework designed to evaluate and improve the security, trustworthiness, and compliance of AI systems. Inspired by OWASP SAMM, AIMA maps AI-specific risks—such as opacity, data poisoning, and model drift—to eight core domains spanning the entire AI lifecycle. Each domain features maturity levels organized into two streams: Create & Promote and Measure & Improve. With assessment worksheets and a scoring methodology, AIMA provides actionable guidance for organizations seeking to embed responsible AI practices, from ethics to secure deployment and operations. It’s tailored for cross-functional teams including CISOs, ML engineers, auditors, and policymakers.
🧩 What’s Covered
AIMA is structured around eight assessment domains, each capturing a vital stage of AI development and operations:
- Responsible AI – Ethical values, transparency, fairness, and societal impact.
- Governance – Strategy, policies, metrics, and cross-role training.
- Data Management – Data quality, governance, accountability, and training practices.
- Privacy – Data minimization, privacy-by-design, user control, and transparency.
- Design – Threat assessment, secure architectures, and security requirements.
- Implementation – Secure build, deployment, and defect management.
- Verification – Security testing, requirement-based validation, and architectural reviews.
- Operations – Incident response, event monitoring, and operational stability.
Each domain is broken into three maturity levels, with Level 1 indicating ad hoc or reactive practices, and Level 3 reflecting continuous, automated, and auditable processes. Activities are grouped into two parallel streams:
- Stream A: Create & Promote – Focuses on embedding practices in teams and workflows.
- Stream B: Measure & Improve – Centers on monitoring, metrics, and iterative refinement.
AIMA provides detailed worksheets and scoring mechanisms to help organizations self-assess or perform external audits. Each worksheet includes criteria per maturity level, enabling both lightweight (yes/no checklist) and detailed(evidence-backed) assessments .
The document also connects AIMA to the broader OWASP AI ecosystem, including:
- OWASP Top 10 for LLM Applications
- OWASP AI Security & Privacy Guide
- OWASP AI Exchange
- OWASP ML Security Top 10
💡 Why it matters?
AI-specific risks—such as non-deterministic behavior, lack of transparency, and data-centric vulnerabilities—often fall outside the scope of traditional maturity models. AIMA fills this gap with a practical, risk-based roadmap for embedding AI governance, enabling organizations to:
- Build audit-ready, privacy-aware, and secure-by-design AI systems.
- Translate abstract ethical principles into measurable practices.
- Align AI governance with evolving regulations (EU AI Act, ISO 42001, NIST AI RMF).
- Promote cross-functional collaboration between legal, technical, and executive stakeholders.
By providing a common language and shared expectations, AIMA helps move the AI governance conversation from principles to concrete engineering decisions—fostering responsible innovation while managing reputational, legal, and operational risks.
❓ What’s Missing
While AIMA excels in scope and structure, several gaps remain:
- Benchmarking data: There’s no public repository or baseline scores for industry comparison.
- Sector-specific guidance: It lacks customization for domains like healthcare or finance.
- Tool integration: Although tooling is mentioned (e.g., SHAP, LIME), detailed examples or references to open-source projects are limited.
- International alignment: Despite referencing EU and NIST frameworks, explicit mapping or concordance tables are missing.
Future versions could also benefit from real-world case studies and guidance for SMEs or startups, which may lack mature governance structures.
👥 Best For
- CISOs and AI security leads creating governance programs
- ML/AI engineers embedding security and fairness into pipelines
- Privacy officers ensuring compliance with GDPR and emerging AI laws
- Risk managers & auditors seeking structured assurance frameworks
- Policy teams translating principles into operational controls
- Consultants conducting AI maturity assessments across clients
📄 Source Details
Title: OWASP AI Maturity Assessment
Version: V1.0 — August 11, 2025
Authors: Matteo Meucci, Philippe Schrettenbrunner (Project Co-Leads), et al.
Publisher: OWASP Foundation
License: Open-source, community-driven
Related Projects: OWASP SAMM, OWASP LLM Top 10, AI Security Guide
📝 Thanks to
Matteo Meucci, Philippe Schrettenbrunner, and the wider OWASP AIMA community for creating a robust, open, and actionable framework that moves the AI governance space forward.
