Objectives: This study aims to explore the role of AI in improving audit quality.Design/method/approach: This study used the Systematic Literature Review (SLR) method to explore the use of AI in auditing. The object of this study was scholarly articles published between 2018-2023. The articles covered the use of AI to optimize the efficiency, accuracy and reliability of the audit process.Results/findings: The results showed that AI is able to automate routine tasks, detect fraud, and identify risks more quickly and accurately than traditional methods. Technologies such as blockchain, machine learning, and advanced data analytics contribute significantly to data-driven decision-making, which improves the overall quality of audits.Theoretical contribution: This research contributes to the literature by expanding the understanding of how AI technologies can improve audit qualityPractical contribution: This research provides practical guidance for auditors and companies to optimally utilize AI technologiesLimitations: This study relies on secondary literature and potential bias in data interpretation, so future research is recommended to explore the empirical impact of AI implementation on audits in different sectors.
                        
                        
                        
                        
                            
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