AI Impact on External Auditor Performance: Electronic Internal Control as a Moderating Variable

Abstract

The rapid adoption of artificial intelligence (AI) in accounting and auditing has transformed traditional audit practices, creating both new opportunities and challenges for external auditors particularly in emerging markets. This study investigates the impact of AI on the performance of external auditors in Jordanian public shareholding service companies, with electronic internal control (EIC) serving as a moderating variable.

A descriptive analytical approach was employed, using a validated 42-item questionnaire distributed to certified public accountants working in Jordanian audit firms. Out of 150 distributed questionnaires, 123 valid responses were obtained (an 82% response rate). Data were analyzed using SPSS software through one-sample t-tests and descriptive statistics.

Results revealed highly significant positive effects of AI across all audit stages: planning (t = 4.867, p < 0.001), control testing (t = 11.131, p < 0.001), analytical procedures (t = 9.977, p < 0.001), audit completion (t = 11.583, p < 0.001), and documentation (t = 12.077, p < 0.001). The overall impact of AI on auditor performance was strongly significant (t = 9.927, p < 0.001). Furthermore, electronic internal control exhibited a significant moderating effect (t = 10.400, p < 0.001), indicating that AI’s effectiveness is amplified in organizations with robust electronic control infrastructures.

These findings provide stage-specific quantitative evidence from an emerging market perspective and offer practical implications for audit firms, client organizations, and policymakers seeking to enhance audit quality and technological integration.