THE IMPACT OF ARTIFICIAL INTELLIGENCE ON INTERNAL CONTROL IN JORDANIAN INDUSTRIAL COMPANIES

Abstract This study endeavored to discern the effect of artificial intelligence on the efficiency and effectiveness of internal control of Jordanian companies of industry. The researchers followed a descriptive-analytic approach. The population of the study encompassed Jordanian public shareholding industrial companies, totaling 46 companies distributed across 9 different industrial sectors. A total of 230 questionnaires were distributed, with an average of 5 questionnaires per company. The study targeted employees in the finance, control and internal audit departments of Jordanian public shareholding industrial companies, specifically those holding positions such as Financial Manager, Head of Accounting Department, Internal Auditor, and Accountant. One of the most significant findings of the study is that the dimensions of artificial intelligence; i.e. (“artificial neural networks”, “machine learning”, “expert systems and genetic algorithms”) affect both the efficiency and effectiveness of internal control in the industrial companies in Jordan. Among the key recommendations made by the researchers is that industrial companies should provide the appropriate infrastructure and specialized training programs to qualify employees to use artificial intelligence tools and techniques to ensure their ability to utilize them effectively.