Audit Your AI Models
Prove What Regulators and Clients Require
Independent technical audits that reduce compliance risk, limit exposure to penalties, and give clients and partners the assurance they need to trust your AI.
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WHAT IS AI MODEL AUDIT
An independent technical assessment that evaluates whether your AI models meet applicable regulatory requirements and technical standards.
An AI Model Audit is conducted against frameworks such as the EU AI Act, NIST AI RMF, and ISO/IEC 42001. It evaluates model performance, data governance, bias and fairness controls, transparency mechanisms, and human oversight structures. The audit independently verifies whether the controls governing your AI models are operative, not just documented, and delivers a structured report you can present to regulators, clients, and investors as evidence of responsible AI governance.
WHY AN AI MODEL AUDIT MATTERS FOR AI COMPLIANCE
Regulatory compliance you can prove
Audit evidence satisfies the conformity requirements of the EU AI Act, NIST AI RMF, and other applicable frameworks. Externally verified, not self-declared.
Reduced exposure to penalties
An audit identifies compliance gaps before regulators do. That difference matters when penalties are on the table.
Trust signal for enterprise clients
Regulated industries require evidence of AI governance before signing contracts. An accredited audit report removes that barrier.
Investor and board assurance
An independent audit gives boards and investors a credible, structured view of how your AI models are governed and controlled.
Clarity on where real risk lives
Audit findings reveal where governance documentation disconnects from actual model behavior. That gap is where liability sits.
A defensible position before any investigation
If a regulator or client asks how your AI was assessed, an accredited third-party audit is the answer that holds.
ROADMAP TO AN AI MODEL AUDIT
Scope & Context Definition
Define the audit boundary, the AI model's intended use, applicable regulatory frameworks, and stakeholder impact.
Documentation Review
Assess technical documentation, risk assessments, data governance records, transparency documentation, and existing control frameworks.
Model Performance & Bias Testing
Evaluate model behavior against defined performance criteria. Assess fairness, robustness, explainability, and alignment with intended use.
Control Effectiveness Review
Evaluate implementation of human oversight mechanisms, monitoring processes, incident response procedures, and operational controls through interviews and evidence review.
Non-Conformity Analysis
Identify and classify findings. Distinguish between gaps in documentation, gaps in implementation, and gaps in operational effectiveness.
Audit Report & Remediation Roadmap
Deliver a structured audit report with findings, root cause analysis, and a prioritized remediation roadmap aligned with applicable regulatory requirements.
Commitment to Excellence
We operate as an accredited, independent assurance body, delivering certifications and audits that regulators, investors, and boards trust.
Accreditation
Accredited as Conformity Assessment Body for AI Management Systems by ANAB (United States) and in the process for UKAS (United Kingdom) and ENAC (Spain - EU).
Credentials
Our team is qualified by leading international organisations for training and certification in AI, data and privacy governance.
Memberships
Member of IAPP, INCITS, UKAI and signatory to the EU AI Pact.
FREQUENTLY ASKED QUESTIONS
What is an AI model audit?
An independent technical assessment that evaluates whether an AI model meets applicable regulatory requirements and technical standards. The output is a structured audit report organizations can present to regulators, clients, and investors.
Which AI models require an audit?
Any AI model used in high-stakes decisions, regulated sectors, or contexts where the EU AI Act, NIST AI RMF, or ISO 42001 apply. This includes models used in hiring, credit scoring, fraud detection, medical diagnosis, and content moderation, among others.
What is the difference between an AI audit and an AI risk assessment?
A risk assessment identifies and evaluates potential risks. An audit independently verifies whether controls to manage those risks are actually in place and working. Both are necessary; they serve different purposes.
How long does an AI model audit take?
A single model audit typically takes between four and six weeks from scoping to report delivery. Complexity, number of models, and documentation readiness affect the timeline.
Does an AI model audit satisfy EU AI Act requirements?
An independent audit by an accredited body provides the evidence base that EU AI Act conformity assessments rely on. For high-risk AI systems, third-party involvement is required in specific categories.
Why does accreditation matter when choosing an AI audit provider?
Accreditation means the body has been independently evaluated for technical competence and impartiality. An audit report from an accredited body carries weight that unaccredited assessments do not.
Can an AI model audit support enterprise sales cycles?
Yes. Procurement and legal teams in regulated industries increasingly require evidence of AI governance before signing contracts. An accredited audit report functions as a trust signal that reduces friction in enterprise sales.
Your fast track to compliance starts here
Our team is ready to support your compliance, cybersecurity, and privacy needs. Complete the contact form or reach out to hello@zertia.ai, and our experts will guide you through the next steps.