Human Judgment in Artificial Intelligence–Assisted Financial Assurance

Benjamin P. Commerford

Human Judgment in Artificial Intelligence–Assisted Financial Assurance

Author(s)	Benjamin P. Commerford
Country	United States
Abstract	Artificial intelligence is increasingly capable of supporting financial assurance through anomaly identification, transaction classification, document analysis, pattern recognition, risk prioritization, and continuous examination of large datasets. These capabilities can increase the scale and efficiency of assurance work, but they do not eliminate the need for professional judgment. Financial assurance frequently requires auditors and other assurance professionals to interpret ambiguous evidence, evaluate materiality, challenge management explanations, recognize unusual business contexts, exercise professional skepticism, and assume responsibility for conclusions that cannot be reduced completely to algorithmic output. This study develops a simulation-based framework for examining the contribution of human judgment in artificial intelligence–assisted financial assurance. Three hypothetical decision architectures are compared: human-only review, AI-led review with limited human challenge, and AI-assisted review incorporating explicit human judgment and professional skepticism. A synthetic analytical sample of 450 observations, equally distributed across the three conditions, is used solely for methodological illustration. Assurance judgment quality, anomaly detection, contextual appropriateness, professional skepticism, review efficiency, and decision confidence are modeled on seven-point scales. The combined architecture therefore outperforms either predominantly human or predominantly automated review within the synthetic model. This result is consistent with pre-2021 audit-technology literature that emphasizes both the analytical capacity of AI and data analytics and the continuing importance of professional skepticism, contextual interpretation, and human expertise. The paper concludes that reliable AI-assisted assurance should preserve human responsibility at points involving materiality, evidence sufficiency, unusual transactions, conflicting signals, management intent, and final assurance conclusions rather than treating human involvement as a residual exception to automation.
Keywords	artificial intelligence; financial assurance; human judgment; auditing; professional skepticism; audit analytics; automation; decision support; assurance quality
Field	Engineering
Published In	Volume 6, Issue 2, March-April 2025
Published On	2025-03-12

View / Download PDF File

About AJAMIR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+1-872-302-3851	editor@ajamir.com

American Journal of Advanced Multidisciplinary Innovation and Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Human Judgment in Artificial Intelligence–Assisted Financial Assurance

Share this