<![CDATA[Penelitian ini bertujuan untuk mengeksplorasi implementasi teknologi Artificial Intelligence (AI) dan automasi dalam proses audit, mengidentifikasi manfaatnya, tantangan yang dihadapi, serta dampaknya terhadap profesi auditor. Penelitian dilakukan menggunakan pendekatan kualitatif melalui metode tinjauan pustaka untuk menganalisis berbagai literatur terkait. Hasil penelitian menunjukkan bahwa AI dan automasi meningkatkan efisiensi, akurasi, serta efektivitas proses audit, terutama dalam analisis data skala besar, deteksi fraud, dan pengambilan keputusan berbasis bukti. Teknologi seperti machine learning, robotic process automation (RPA), dan blockchain memainkan peran penting dalam menyederhanakan tugas audit. Namun, penerapan AI juga menghadapi tantangan, termasuk kebutuhan akan keahlian teknis, investasi teknologi, serta isu privasi dan keamanan data. Penelitian ini menemukan bahwa peran auditor tetap esensial dalam pengambilan keputusan berbasis penilaian profesional yang kompleks. Integrasi teknologi membutuhkan penyesuaian pada kompetensi auditor, transformasi metodologi audit, serta penyesuaian regulasi yang relevan. Saran untuk penelitian lanjutan meliputi pengembangan model penerapan AI yang lebih efektif dan kajian mendalam terkait dampak sosial dan etika dari teknologi ini dalam audit. This study aims to explore the implementation of Artificial Intelligence (AI) and automation technology in the audit process, identify its benefits, challenges faced, and its impact on the auditor profession. The study was conducted using a qualitative approach through a literature review method to analyze various related literature. The results of the study indicate that AI and automation improve the efficiency, accuracy, and effectiveness of the audit process, especially in large-scale data analysis, fraud detection, and evidence-based decision making. Technologies such as machine learning, robotic process automation (RPA), and blockchain play an important role in simplifying audit tasks. However, the implementation of AI also faces challenges, including the need for technical expertise, technology investment, and data privacy and security issues. This study found that the role of auditors remains essential in complex professional judgment-based decision making. Technology integration requires adjustments to auditor competencies, transformation of audit methodology, and adjustments to relevant regulations. Suggestions for further research include the development of a more effective AI implementation model and an in-depth study of the social and ethical impacts of this technology in audits.]]>
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