Research on the Application of Artificial Intelligence in Audit Risk Assessment DOI
Ruixue Yang

Published: April 9, 2025

With the rapid advancement of artificial intelligence (AI) technology, China has entered an era where AI profoundly impacts various aspects socioeconomic development. As a critical component enterprise risk management, audit assessment faces significant transformation opportunities driven by AI. This study systematically reviews application in assessment, analyzing its current development status, operational advantages, and practical challenges. By synthesizing research findings across multiple disciplines, this paper identifies that enhances efficiency through real-time data analysis, automated identification, intelligent decision support. However, challenges such as quality technical complexity, workforce adaptation remain barriers. The concludes future should focus on integrating with emerging technologies, transforming traditional models toward monitoring, cultivating interdisciplinary professionals to address evolving industry demands. These insights provide theoretical foundations guidance for optimizing adoption assessment.

Language: Английский

Digital Transformation and the Future of Accounting DOI
Siriyama Kanthi Herath,

Susan White

Advances in business strategy and competitive advantage book series, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 34

Published: Jan. 31, 2025

This research explores effects of artificial intelligence (AI) on the accounting profession in Asia, Europe and Gulf Region. It examines state digital adoption these regions, factors that affect rates adoption, issues prospects. Diffusion Innovation Theory is used as theoretical basis by which various influencing integration AI are identified. identifies advantages use include improved quality speed work, but drawbacks high costs lack skills to implement solutions. also tries anticipate future outcomes such shift roles employment heightened rivalry.

Language: Английский

Citations

0
Transforming Auditing through AI and Blockchain: A Comprehensive Study on Adoption, Implementation, and Impact in Financial Audits DOI Open Access

Muhammad Arham

American Journal of Industrial and Business Management, Journal Year: 2025, Volume and Issue: 15(02), P. 225 - 241

Published: Jan. 1, 2025

Language: Английский

Citations

0
From AI Knowledge to AI Usage Intention in the Managerial Accounting Profession and the Role of Personality Traits—A Decision Tree Regression Approach DOI Open Access
Lavinia Denisia Cuc, Dana Rad,

Teodor Florin Cilan

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(6), P. 1107 - 1107

Published: March 11, 2025

This study examines the key drivers behind adoption of artificial intelligence (AI) in accounting profession, emphasizing influence AI-related knowledge, personality traits, and professional roles. By applying Decision Tree Regression analysis to survey data from professionals, our research identifies AI knowledge as strongest determinant adoption, underscoring importance expertise technology acceptance. While traits play a secondary role, extraversion openness emerge significant factors influencing intentions. The further explores applications financial auditing, tax compliance, fraud detection, clarifying specific domains impacted by integration. These findings offer valuable guidance for policymakers, educators, business leaders aiming equip workforce with necessary skills mindset navigate AI-driven transformation profession.

Language: Английский

Citations

0
Research on the Application of Artificial Intelligence in Audit Risk Assessment DOI
Ruixue Yang

Published: April 9, 2025

With the rapid advancement of artificial intelligence (AI) technology, China has entered an era where AI profoundly impacts various aspects socioeconomic development. As a critical component enterprise risk management, audit assessment faces significant transformation opportunities driven by AI. This study systematically reviews application in assessment, analyzing its current development status, operational advantages, and practical challenges. By synthesizing research findings across multiple disciplines, this paper identifies that enhances efficiency through real-time data analysis, automated identification, intelligent decision support. However, challenges such as quality technical complexity, workforce adaptation remain barriers. The concludes future should focus on integrating with emerging technologies, transforming traditional models toward monitoring, cultivating interdisciplinary professionals to address evolving industry demands. These insights provide theoretical foundations guidance for optimizing adoption assessment.

Language: Английский

Citations

0