Audit sampling has become one of the most widely applied techniques in modern auditing because it enables auditors to obtain sufficient and appropriate audit evidence efficiently. However, the use of audit sampling also introduces sampling risk, which may lead auditors to reach conclusions that differ from those that would have been obtained if the entire population had been examined. This study aims to analyze the role of audit sampling risk in detecting material misstatements during tests of controls through a literature review approach. The research employed qualitative descriptive methods using secondary data collected from scientific journals, international auditing standards, books, and previous empirical studies published between 2020 and 2025. The collected literature was analyzed through content analysis to identify similarities, differences, and developments related to audit sampling practices. The findings indicate that sampling risk significantly influences the reliability of auditors' conclusions regarding internal control effectiveness. Statistical sampling techniques generally provide more reliable audit evidence compared to non-statistical sampling because they allow auditors to quantify sampling risk objectively. Furthermore, technological developments, such as audit data analytics, have contributed to reducing sampling risk by enabling broader examination of transaction populations. The study concludes that proper audit planning, appropriate sampling techniques, and professional judgment are essential to minimize sampling risk and improve audit quality.