The industrial revolution (4.0) has seen a rapid advancement in technology. The existence of machine learning and artificial intelligence is one of them. By automating most audit processes with AI, auditors can increase efficiency and accuracy. AI-powered technology reduces human error risk while speeding up the auditing process. The outcome is more timely and accurate information sent to the management. Nonetheless, auditors were still using artificial intelligence and machine learning in very small amounts. Furthermore, specialized research on this subject is still scarce. We wish to investigate this research gap. We study what influences artificial intelligence and machine learning adoption by auditors. Based on Diffusion of Innovation Theory, we employ constructs or variables. Structural equation modeling partial least squares is used in data analysis for our quantitative research. By giving questionnaires to Jakarta public accounting firms’ auditors, we can gather primary data. We use the statistical method of partial least squares for structural equation modeling when analyzing data. The software we use is SMART PLS version 4. The findings of our study show that the relative advantage, compatibility, trialability, and observability of each have a big impact on the auditor’s adoption of artificial intelligence and machine learning.
 

Link: Diffusion of Innovation on Auditor Adoption of Artificial Intelligence and Machine Learning