Toward a More Reliable Standard for AI-Assisted Audits
Make AI-Assisted Audit Results Useful for Decisions.
AI responses are useful. But in audits and other important verification work, an answer alone is not enough.
What evidence supports the conclusion? Have the identified issues been resolved? What remains unverified?
7200core is a technology foundation being developed to clarify this information and improve thereliability and practical value of AI-assisted audits.
Four Key Features of 7200core
01 | Look Beyond Conclusions to Evidence
Review audit findings and supporting evidence rather than making decisions from conclusions alone.
02 | Keep Unresolved and Unverified Items Visible
Maintain a clear distinction between failed checks, unverified items, resolved issues, and outstanding work.
03 | Revisit Earlier Results After Changes
When documents or review targets change, previous findings remain useful for understanding what has and has not been checked.
04 | Preserve Human Final Judgment
Support human decisions on adoption and approval after reviewing the necessary information, rather than relying solely on AI responses.
Our Objective
Our objective is not simply to have AI say “no issues found.”
It is to make verified information, unresolved issues, and relevant evidence available for review.
The goal of 7200core is not AI usage for its own sake, but greater reliability in work performed with AI.
Current Development Status
7200core is currently in development and validation.
Effects on audit quality, work time, and cost will be assessed through comparative validation. Commercial release dates and terms have not been determined.