← Search

Journal of Accounting Research Vol. 60 No. 1 2022

Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence

Benjamin P. Commerford1; Sean A. Dennis2; Jennifer R. Joe3; JENNY W. ULLA4

1 University of Kentucky · 2 University of Central Florida · 3 University of Delaware · 4 University of Nevada, Las Vegas

Abstract

Audit firms are investing billions of dollars to develop artificial intelligence (AI) systems that will help auditors execute challenging tasks (e.g., evaluating complex estimates). Although firms assume AI will enhance audit quality, a growing body of research documents that individuals often exhibit “algorithm aversion”—the tendency to discount computer‐based advice more heavily than human advice, although the advice is identical otherwise. Therefore, we conduct an experiment to examine how algorithm aversion manifests in auditor judgments. Consistent with theory, we find that auditors receiving contradictory evidence from their firm's AI system (instead of a human specialist) propose smaller adjustments to management's complex estimates, particularly when management develops their estimates using relatively objective (vs. subjective) inputs. Our findings suggest auditor susceptibility to algorithm aversion could prove costly for the profession and financial statements users.

DOI
10.1111/1475-679x.12407
Volume
60
Issue
1
Pages
171-201
Language
en
Sources
bibtex:phds-export.bib openalex crossref

Cite