AI in SOC Examinations: Automation & Audit Judgment
October 27, 2026Automate the routine while keeping professional judgment at the center of every SOC opinion. Artificial intelligence (AI) and machine learning are changing how assurance is delivered, moving service auditors from manual evidence gathering toward the areas of highest risk and complexity. Automated data validation, population testing, and API-driven evidence integration can help reduce the burden on service organizations while strengthening the reliability of the information behind each conclusion.
This session examines where automation fits across the SOC 1 and SOC 2 lifecycle and where human judgment stays non-negotiable. We’ll look at how AI can test larger sets of data, not just small samples. We’ll also cover three key practices: staying skeptical of results, confirming that Information Produced by the Entity (IPE) is complete and accurate, and tying each conclusion back to its original source. Service organizations that understand these shifts can prepare for a smoother, less disruptive examination without trading away audit quality.
Learning Objectives
Upon completion of this program, participants should be able to:
- Identify where AI and machine learning can add value across SOC 1 and SOC 2 procedures, from three-way matching to configuration baselining and log analysis.
- Describe the controls that preserve audit integrity when automation is used, including model validation and professional skepticism.
- Recognize how completeness and accuracy of IPE apply to AI-driven processes, spanning IT applications, end-user computing, service organizations, and manual processes.
Presenters
