Introducing Mend.io’s AI Security Maturity Survey + Compliance Checklist available today

Today, we’re excited to launch two practical tools to help teams quickly understand their AI maturity, quantify AI risk, and gather the evidence executives will ask for in 2026: an interactive AI Security Maturity Survey (with a personalized score and mapped recommendations) and a companion AI Security Compliance Checklist. Both are aligned to industry standards and built to be immediately useful in discovery, audits, and planning.

Why this matters right now

Regulation and auditor expectations are moving fast. Frameworks and rules, such as OWASP AIMA, NIST AI RMF, ISO/IEC 42001, and the EU AI Act, are becoming the default checklists that auditors and CISOs use to judge AI programs. Enforcement bodies for the EU AI Act go live in August 2026, and mandatory incident-reporting timelines are arriving soon. That means teams must not only build safe AI, but they must document and prove it. Our survey and checklist are designed to help you do exactly that: find gaps, prioritize fixes, and generate audit-ready artifacts.

What you’ll get

1. Interactive AI security maturity survey

• A short (~5-minute) self-assessment that benchmarks your AI security posture against the major frameworks (OWASP AIMA, NIST AI RMF, ISO 42001, EU AI Act).
• A personalized maturity level (Emerging → Developing → Controlling → Leading) and a prioritized roadmap of what to fix next.
• Concrete, framework-mapped recommendations you can share with leadership or auditors.

2. AI security compliance checklist

A practical, checklist-style toolkit you can use in audits. Key groups include:

• Governance & accountability: define owners, policies, risk register, and human oversight.
• AI inventory & risk identification: create and maintain an AI Bill of Materials (AI BoM), threat modeling, and pre-deployment risk assessments.
• Security & technical controls: input/output validation to prevent prompt injection, access controls, encryption, continuous red teaming, and SDLC integration.
• Transparency & lifecycle assurance: model cards, decision logging, AIWE (AI Weakness) scoring, runtime monitoring, bias & fairness checks.
• Continuous improvement & compliance proof: incident response, audits, corrective-action tracking, post-market monitoring.

Use this checklist as a practical “what to do next” guide or as a live worksheet in a discovery session.

How to interpret your survey result (and what to do next)

The survey places you on a four-stage maturity scale. Here’s how to read each stage and the immediate, low-friction next step:

• Emerging– No inventory, little governance, minimal behavioral testing.
  First move: Build visibility. Start an AI BoM to answer the question: “What AI do we actually have?” Visibility is the foundation: you can’t secure what you don’t know.
• Developing– Some policies and manual controls, inconsistent enforcement.
  First move: Standardize guardrails. Adopt system prompt detection/hardening and enforce policy for LLMs so that developer velocity doesn’t mean risk.
• Controlling– Formal controls, partial automation, and early testing.
  First move: Add adversarial realism. Move from periodic checks to continuous validation, automated red teaming, and AIWE scoring to catch behavioral risks.
• Leading– Mature governance, continuous monitoring, proof for auditors.
  First move: Demonstrate and document assurance. Focus on scalable reporting, audit artifacts, and lifecycle controls to prove safety at scale.

What the survey report includes

This tactical tool is designed so you can run this as part of an internal risk review or bring it to a governance committee. When you finish the assessment, you’ll get:

• A maturity level and a short explanation of what it means for your program.
• A prioritized list of fixes mapped to OWASP AIMA, NIST AI RMF, ISO 42001, and the EU AI Act.
• Practical CTAs tailored to your level (visibility → guardrails → continuous testing → assurance).

For security teams responsible for audits or procurement

If you’re preparing for third-party review or procurement conversations, use the checklist to generate audit artifacts: an AI BoM, model cards, runbooks for human oversight and incident response, red team reports, and runtime monitoring logs. These items map directly to what auditors will ask for under the EU AI Act and other standards.

Where to start

Take the survey: mend.io/ai-security-survey

This is a resource for teams that need to map current practices to compliance requirements and build a defensible plan. If you want, run the assessment with your team and bring the results to your next governance meeting. The first step is almost always simply documenting what you have and where it’s used. This will help you take that step!