XAI Audit
A review process that evaluates whether AI explainability outputs meet internal policies and regulatory requirements, ensuring sufficient transparency.
A systematic examination - by internal compliance teams or external auditors - of explanation artifacts, comparing them against policy checklists (e.g., “Does every high-risk decision include a counterfactual explanation?”), regulatory mandates (e.g., GDPR right to explanation), and stakeholder needs. The audit assesses both technical correctness and usability, documents findings, and issues remediation plans for any gaps in explanation coverage or quality.
A financial regulator conducts an XAI Audit on a bank’s credit-scoring AI. Auditors sample denials, review corresponding explanations, verify that each includes clear rationales and remedial suggestions, and confirm that explanation logs are retained for the required five-year period. Any missing or inadequate explanations prompt corrective action by the bank.
We help you find answers
What problem does Enzai solve?
Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
Who is Enzai built for?
How is Enzai different from other governance tools?
Can we start if we have no existing AI governance process?
Does AI governance slow down innovation?
How does Enzai stay aligned with evolving AI regulations?
Research, insights, and updates
Empower your organization to adopt, govern, and monitor AI with enterprise-grade confidence. Built for regulated organizations operating at scale.