When collecting data for analysis by AI tools in an audit, the MOST important immediate consideration is that thedata format and syntaxalign with therequirements of the AI tools(C). Without correct formatting (e.g., structured fields, correct data types, consistent delimiters, proper encoding), AI tools may fail, misinterpret data, or generate unreliable results. AAIA’s domain on AI in audit processes stressesdata preparation, cleansing, and transformationas critical steps before applying AI analytics.

Data classification (A) and access restrictions (B) are significant from a security and privacy standpoint, but for the AI analysis itself to function correctly, theformat/syntaxis foundational. Model weights (D) relate to the AI training phase, not to the auditor’s data collection step. Thus, ensuring thedata provided to AI audit tools is properly structured and syntactically compatibleis the primary technical concern.