Artificial Intelligence (AI) is transforming risk assessment in audit planning and execution, offering significant improvements in efficiency, accuracy, and strategic decision-making. This review explores the role of AI-driven risk assessment in revolutionizing the audit process, highlighting its benefits and challenges. AI technologies, particularly machine learning and advanced data analytics, enhance auditors' ability to identify, assess, and manage risks. Traditional methods rely on historical data and static models, which are limited in predictive power. In contrast, AI-driven approaches use vast datasets, continuously updating and learning from new information to provide dynamic and precise risk evaluations. AI enables auditors to process large volumes of data rapidly, identifying patterns and anomalies that may indicate potential risks. This capability ensures more comprehensive and accurate risk assessments, allowing auditors to focus on high-risk areas and allocate resources effectively. AI also enhances strategic audit planning by providing real-time insights into emerging risks, enabling proactive risk management. Despite these advantages, integrating AI into risk assessment poses challenges, including data quality, transparency, and ethical considerations. Ensuring data integrity is crucial, as AI systems rely on accurate information. The "black box" nature of some AI models can create transparency issues, making it difficult for auditors to explain risk assessments. Addressing algorithmic biases and ensuring regulatory compliance are also critical. AI-driven risk assessment is revolutionizing audit planning and execution by improving risk detection and management. However, auditors must navigate challenges related to data quality, transparency, and ethics to fully realize AI's potential. By leveraging AI, auditors can enhance audit quality, improve efficiency, and adapt to the complexities of modern business environments. The integration of AI into audit processes is a rapidly evolving trend with significant implications for audit practices. As AI technology advances, its potential to enhance audit processes in terms of efficiency, accuracy, and scope is substantial. Organizations that successfully implement AI-driven risk assessment can gain a competitive advantage and strengthen their risk management capabilities. The future of auditing involves a significant integration of AI tools, focusing on enhancing efficiency, accuracy, and risk assessment capabilities. Auditors who embrace AI technologies are well-positioned to drive innovation and excel in the evolving audit landscape.Artificial Intelligence (AI) is transforming risk assessment in audit planning and execution, offering significant improvements in efficiency, accuracy, and strategic decision-making. This review explores the role of AI-driven risk assessment in revolutionizing the audit process, highlighting its benefits and challenges. AI technologies, particularly machine learning and advanced data analytics, enhance auditors' ability to identify, assess, and manage risks. Traditional methods rely on historical data and static models, which are limited in predictive power. In contrast, AI-driven approaches use vast datasets, continuously updating and learning from new information to provide dynamic and precise risk evaluations. AI enables auditors to process large volumes of data rapidly, identifying patterns and anomalies that may indicate potential risks. This capability ensures more comprehensive and accurate risk assessments, allowing auditors to focus on high-risk areas and allocate resources effectively. AI also enhances strategic audit planning by providing real-time insights into emerging risks, enabling proactive risk management. Despite these advantages, integrating AI into risk assessment poses challenges, including data quality, transparency, and ethical considerations. Ensuring data integrity is crucial, as AI systems rely on accurate information. The "black box" nature of some AI models can create transparency issues, making it difficult for auditors to explain risk assessments. Addressing algorithmic biases and ensuring regulatory compliance are also critical. AI-driven risk assessment is revolutionizing audit planning and execution by improving risk detection and management. However, auditors must navigate challenges related to data quality, transparency, and ethics to fully realize AI's potential. By leveraging AI, auditors can enhance audit quality, improve efficiency, and adapt to the complexities of modern business environments. The integration of AI into audit processes is a rapidly evolving trend with significant implications for audit practices. As AI technology advances, its potential to enhance audit processes in terms of efficiency, accuracy, and scope is substantial. Organizations that successfully implement AI-driven risk assessment can gain a competitive advantage and strengthen their risk management capabilities. The future of auditing involves a significant integration of AI tools, focusing on enhancing efficiency, accuracy, and risk assessment capabilities. Auditors who embrace AI technologies are well-positioned to drive innovation and excel in the evolving audit landscape.