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Relevant bibliographies by topics / AI auditing

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Academic literature on the topic 'AI auditing'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "AI auditing"

1

Muftah, Mohammed Abu Reemah Ahmed. "The Impact of Artificial Intelligence on Auditing Practices and Financial Reporting Accuracy." Integrated Journal for Research in Arts and Humanities 2, no. 1 (2022): 40–46. http://dx.doi.org/10.55544/ijrah.2.1.49.

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The transformational effects of artificial intelligence (AI) on auditing procedures and financial reporting accuracy are examined in this study article. This research looks at how artificial intelligence (AI) tools, such data analytics and machine learning, are changing auditing by making it more efficient, lowering the risk of human mistake, and boosting the ability to spot fraud. The study outlines the advantages and difficulties of using AI in auditing via a thorough examination of the literature and an analysis of current trends. Based on important discoveries, AI-powered audits may greatl

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Lassiter, Tina B., and Kenneth R. Fleischmann. ""Something Fast and Cheap" or "A Core Element of Building Trust"? - AI Auditing Professionals' Perspectives on Trust in AI." Proceedings of the ACM on Human-Computer Interaction 8, CSCW2 (2024): 1–22. http://dx.doi.org/10.1145/3686963.

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Artificial Intelligence (AI) auditing is a relatively new area of work. Currently, there is a lack of uniform standards and regulation. As a result, the AI auditing ecosystem is very diverse, and AI auditing professionals use a variety of different auditing methods. So far, little is known about how AI auditors approach the concept of trust in AI through AI audits, in particular regarding the trust of users. This paper reports findings from interviews with 19 AI auditing stakeholders to understand how AI auditing professionals seek to create calibrated trust in AI tools and AI audits. Themes i

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Friday, Solomon Christopher, Maxwell Nana Ameyaw, and Temitayo Oluwaseun Jejeniwa. "A Conceptual Framework for Integrating Artificial Intelligence in Financial Auditing Practices." International Journal of Social Science Exceptional Research 2, no. 1 (2023): 172–82. https://doi.org/10.54660/ijsser.2023.2.1.172-182.

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The integration of Artificial Intelligence (AI) into financial auditing has revolutionized traditional auditing methods by enhancing efficiency, accuracy, and fraud detection. This presents a conceptual framework for incorporating AI technologies into financial auditing practices, highlighting key applications, challenges, and strategic implementation. AI-driven tools such as Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA) enable auditors to process large datasets, detect anomalies, and predict financial risks with greater precision. These technol

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Leocádio, Diogo, Luís Malheiro, and João Reis. "Artificial Intelligence in Auditing: A Conceptual Framework for Auditing Practices." Administrative Sciences 14, no. 10 (2024): 238. http://dx.doi.org/10.3390/admsci14100238.

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The transition to digital business systems has revolutionized organizational operations, driven by the integration of advanced technologies such as artificial intelligence (AI). This integration indicates a shift, redefining traditional practices and enhancing efficiency across diverse sectors such as finance, healthcare, and manufacturing. This study explores the impact of AI on auditing through a systematic literature review to develop a conceptual framework for auditing practices. The theoretical implications show the transformative role of AI in redefining auditors’ roles, shifting from re

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Ramadhan Mukhtar, Multazam, Andi Muhammad Syahrul, and Ahmad Habibi. "Penerapan Audit Berbasis Artificial Intelligence di Indonesia: Sebuah Metasintetis." Journal of Economic Education and Entrepreneurship Studies 4, no. 2 (2023): 711–28. http://dx.doi.org/10.26858/je3s.v4i2.1852.

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This research aims to find out how the application of advanced artificial intelligence technology in conducting audits in Indonesia. The method used by the analysis tool is a metasynthesis of a number of qualitative studies on AI-based auditing. The results of this study provide new insights into the barriers, conveniences, challenges, and opportunities in the application of AI-based auditing in Indonesia. Auditors face barriers to implementing AI technology, which involves adjusting their skills and experience. Challenges in implementing AI-based auditing include technical aspects, skills, et

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Fidyah, Feny, Susanti Usman, Afrila Eki Pradita, and Dyah Mieta Setyawati. "The Impact of Artificial Intelligence on Auditing Processes and Accuracy: A Future Outlook." Dinasti International Journal of Economics, Finance & Accounting 5, no. 4 (2024): 4350–58. https://doi.org/10.38035/dijefa.v5i4.3224.

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Artificial Intelligence (AI) is revolutionizing auditing processes, promising significant improvements in accuracy, efficiency, and risk management. This literature review explores the transformative impact of AI on auditing practices and outlines future prospects. AI technologies such as machine learning, natural language processing, and robotic process automation are being integrated into auditing systems, enabling real-time data analysis, anomaly detection, and predictive insights. These advancements not only enhance traditional auditing methodologies but also introduce new approaches capab

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Ganapathy, Venkatasubramanian. "AI in Auditing: A Comprehensive Review of Applications, Benefits and Challenges." Shodh Sari-An International Multidisciplinary Journal 02, no. 04 (2023): 328–43. http://dx.doi.org/10.59231/sari7643.

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The rapid evolution of artificial intelligence (AI) technologies has brought about transformative changes in various industries, and the field of auditing is no exception. This research paper presents a comprehensive review of the integration of AI in auditing practices, highlighting its applications, benefits, and associated challenges. Auditing, a critical process for ensuring the accuracy and reliability of financial information, has traditionally been a labor-intensive and time-consuming endeavor. The emergence of AI technologies, such as machine learning, natural language processing, and

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Kumar Gupta, Dr Anoop, and Pankaj Agarwal. "Present and Future Perspective of AI Audit in India." Journal Global Value XVI, SI (2025): 237–48. https://doi.org/10.31995/jgv.2025.v16isi7.031.

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In the rapidly evolving auditing sector, AI-powered technologies are revolutionising traditional practices. As the industry is changing due to new regulations and emerging technologies, many auditors are having difficulty with out-dated practices and inefficiencies. More advanced technology has never been needed for modern auditing, and artificial intelligence (AI) is setting the standard for this advancement. There are intriguing opportunities to improve the efficacy, impact, and efficiency of internal auditors’ work with artificial intelligence in auditing. To use AI effectively, auditors mu

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Mökander, Jakob, and Luciano Floridi. "Ethics-Based Auditing to Develop Trustworthy AI." Minds and Machines 31, no. 2 (2021): 323–27. http://dx.doi.org/10.1007/s11023-021-09557-8.

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AbstractA series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing

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Olubusola Odeyemi, Kehinde Feranmi Awonuga, Noluthando Zamanjomane Mhlongo, Ndubuisi Leonard Ndubuisi, Funmilola Olatundun Olatoye, and Andrew Ifesinachi Daraojimba. "The role of AI in transforming auditing practices: A global perspective review." World Journal of Advanced Research and Reviews 21, no. 2 (2023): 359–70. http://dx.doi.org/10.30574/wjarr.2024.21.2.0460.

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This Review provides a glimpse into the comprehensive examination of the transformative impact of Artificial Intelligence (AI) on auditing practices globally. The review delves into the multifaceted ways in which AI technologies are reshaping traditional auditing methodologies, bringing about efficiency, accuracy, and adaptability in the face of an evolving business landscape. The global perspective of this review encompasses diverse industries and jurisdictions, offering insights into how AI is redefining the audit landscape on a universal scale. The analysis explores the integration of AI-dr

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Dissertations / Theses on the topic "AI auditing"

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Provençal, Christiane. "Caractéristiques fonctionnelles des cellules de projection et de réception calleuse du cortex auditif AI chez le chat." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq26720.pdf.

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Books on the topic "AI auditing"

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Erasmus, Lourens J., and Sezer Bozkus Kahyaoğlu. Continuous Auditing with AI in the Public Sector. CRC Press, 2024. http://dx.doi.org/10.1201/9781003382706.

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Ekukinam, Chinedu. IT Auditing for AI/ML and Robotics Process Automation. Lulu Press, Inc., 2023.

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AI Management System Auditing and Compliance According to the ISO/IEC 42001 Standard: How to Audit, Certify, and Build Responsible AI Systems. Productivity Press, 2024.

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AI Management System Auditing and Compliance According to the ISO/IEC 42001 Standard: How to Audit, Certify, and Build Responsible AI Systems. Productivity Press, 2024.

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AI Management System Auditing and Compliance According to the ISO/IEC 42001 Standard: How to Audit, Certify, and Build Responsible AI Systems. Productivity Press, 2024.

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AI Management System Auditing and Compliance According to the ISO/IEC 42001 Standard: How to Audit, Certify, and Build Responsible AI Systems. Productivity Press, 2024.

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7

Becker Castellaro, Sebastian, Mariana Carvalho, Alberto Fernandez Gibaja, et al. Artificial Intelligence and Information Integrity: Latin American experiences. Policy Paper No. 34, 2025. International Institute for Democracy and Electoral Assistance (International IDEA) and Fundação Getulio Vargas—Comunicação, 2025. https://doi.org/10.31752/idea.2025.39.

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This policy paper examines the impact of artificial intelligence (AI) on information integrity in electoral contexts across Latin America. Drawing on case studies from Brazil’s and Mexico’s 2024 elections, it analyses how AI tools are used to create, curate and moderate political content online, with particular attention to their effects on marginalized groups such as women, Indigenous communities and LGBTQIA+ individuals. While the use of generative AI in elections remains limited, its potential to undermine democratic discourse and amplify harmful content demands urgent attention. To protect

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Book chapters on the topic "AI auditing"

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Sayles, James. "Auditing AI Systems." In Principles of AI Governance and Model Risk Management. Apress, 2024. https://doi.org/10.1007/979-8-8688-0983-5_18.

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Pierotti, Mariarita. "AI for Financial Accounting." In Artificial Intelligence in Accounting and Auditing. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-71371-2_7.

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Pierotti, Mariarita. "AI for Managerial Accounting." In Artificial Intelligence in Accounting and Auditing. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-71371-2_8.

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Naoufal, Georges. "Continuous auditing/continuous monitoring." In Continuous Auditing with AI in the Public Sector. CRC Press, 2024. http://dx.doi.org/10.1201/9781003382706-9.

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Adams, Carl, Mohsen Eslamnejad, Anita Khadka, Andrew M’manga, Heather Shaw, and Yuchen Zhao. "Auditing AI Systems: A Metadata Approach." In Artificial Intelligence XL. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47994-6_22.

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van Wingerden, A. B., and H. Weigand. "AI Auditing: Towards a Practicable Model." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-92471-2_14.

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Schöppl, Noah, Mariarosaria Taddeo, and Luciano Floridi. "Ethics Auditing: Lessons from Business Ethics for Ethics Auditing of AI." In The 2021 Yearbook of the Digital Ethics Lab. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09846-8_13.

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Becker, Nikolas, and Bernhard Waltl. "Auditing and Testing AI – A Holistic Framework." In Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Health, Operations Management, and Design. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06018-2_20.

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Whig, Pawan, Shama Kouser, Ashima Bhatnagar Bhatia, Rahul Reddy Nadikattu, and Radhika Mahajan. "Amalgamation of AI and Blockchain in Auditing." In Advanced Digital Technologies in Financial and Business Management. Apple Academic Press, 2025. https://doi.org/10.1201/9781003558279-10.

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Modisane, Cameron. "Background information about AI in accounting and auditing practice." In Continuous Auditing with AI in the Public Sector. CRC Press, 2024. http://dx.doi.org/10.1201/9781003382706-2.

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Conference papers on the topic "AI auditing"

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Kevin, Jun, and Pujianto Yugopuspito. "SmartLLM: Smart Contract Auditing using Custom Generative AI." In 2025 International Conference on Computer Sciences, Engineering, and Technology Innovation (ICoCSETI). IEEE, 2025. https://doi.org/10.1109/icocseti63724.2025.11019687.

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Yuan, Chih-Cheng Rex, and Bow-Yaw Wang. "Ensuring Fairness with Transparent Auditing of Quantitative Bias in AI Systems." In 2024 Pacific Neighborhood Consortium Annual Conference and Joint Meetings (PNC). IEEE, 2024. http://dx.doi.org/10.23919/pnc63053.2024.10697374.

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Dawood, Anmar Noori, and Akeel ALmagtome. "Impact of AI on Auditing: Transforming Assurance Services in the Digital Age." In 2025 International Conference on Frontier Technologies and Solutions (ICFTS). IEEE, 2025. https://doi.org/10.1109/icfts62006.2025.11031604.

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Mushtaq, Abdullah, Rafay Naeem, Imran Taj, Ibrahim Ghaznavi, and Junaid Qadir. "Towards Inclusive Educational AI: Auditing Frontier LLMs for Cultural Biases through a Multiplexity Lens." In 2025 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2025. https://doi.org/10.1109/educon62633.2025.11016405.

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Solyst, Jaemarie, Cindy Peng, Wesley Hanwen Deng, et al. "Investigating Youth AI Auditing." In FAccT '25: The 2025 ACM Conference on Fairness, Accountability, and Transparency. ACM, 2025. https://doi.org/10.1145/3715275.3732142.

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Galdon Clavell, Gemma, Mariano Martín Zamorano, Carlos Castillo, Oliver Smith, and Aleksandar Matic. "Auditing Algorithms." In AIES '20: AAAI/ACM Conference on AI, Ethics, and Society. ACM, 2020. http://dx.doi.org/10.1145/3375627.3375852.

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Raji, Inioluwa Deborah, and Joy Buolamwini. "Actionable Auditing." In AIES '19: AAAI/ACM Conference on AI, Ethics, and Society. ACM, 2019. http://dx.doi.org/10.1145/3306618.3314244.

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Cachel, Kathleen, and Elke Rundensteiner. "FINS Auditing Framework." In AIES '22: AAAI/ACM Conference on AI, Ethics, and Society. ACM, 2022. http://dx.doi.org/10.1145/3514094.3534160.

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Butt, AYesha, Aisha Zahid Junejo, Sumbul Ghulamani, Ghulam Mahdi, Asadullah Shah, and Dodo Khan. "Deploying Blockchains to Simplify AI Algorithm Auditing." In 2023 IEEE 8th International Conference on Engineering Technologies and Applied Sciences (ICETAS). IEEE, 2023. http://dx.doi.org/10.1109/icetas59148.2023.10346420.

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Rajković, Siniša. "AI U REVIZIJI – PROMJENA TRADICIONALNOG PRISTUPA PROVJERE FINANSIJSKIH IZVJEŠTAJA." In 5. naučni skup Računovodstvena znanja kao činilac ekonomskog i društvenog napretka. Ekonomski fakultetUniverziteta u Kragujevcu, 2025. https://doi.org/10.46793/rz25.469r.

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This paper explores the role and application of artificial intelligence (AI) in the audit of financial statements, with a particular focus on practical examples from modern auditing practice. The technological aspect of AI includes tools such as machine learning, big data analytics, and process automation, which enable auditors to gain deeper insight into financial information. The paper analyzes the benefits of AI implementation, including increased efficiency, more accurate detection of irregularities, and enhanced opportunities for continuous auditing. At the same time, challenges such as d

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Reports on the topic "AI auditing"

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Faveri, Benjamin, Maureen Johnson-León, Prem Sylvester, et al. Towards A Global AI Auditing Framework: Assessment and Recommendations. Edited by Luis Adrián Castro-Quiroa, Eloísa Gacía-Canseco, Joan Hassan, et al. International Panel on the Information Environment (IPIE), 2025. https://doi.org/10.61452/zwed1485.

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A high-level précis of the Synthesis Report can be found in the Summary for Policymakers Recommendations for a Global AI Auditing Framework: Summary of Standards and Features. The growing integration of artificial intelligence (AI) into critical sectors of society, from healthcare to education, has the potential to support widespread social transformation and progress. However, AI systems also have the power to perpetuate biases, deepen inequalities, and cause environmental harm. Accurately evaluating the risks and benefits of an AI system requires a careful audit. Current approaches to auditi

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Sylvester, Prem, Wendy Hui Kyong Chun, Anikó Hannák, et al. Global Approaches to Auditing Artificial Intelligence: A Literature Review. Edited by Danaë Metaxa, Jack Bandy, Luis Adrián Castro-Quiroa, et al. International Panel on the Information Environment (IPIE), 2024. https://doi.org/10.61452/bwym7397.

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This Synthesis Report is a literature review outlining the regulatory, industry, and academic approaches to AI audits. We review 78 articles published in peer-reviewed journals and as preprints, 21 documents from industry associations and standard-setting organizations, and national policy documents and regulations from 20 countries. Based on this review, we identify three key takeaways about the landscape of AI auditing: 1. To accurately assess the potential risks, and impacts of AI systems, we need a trustworthy audit ecosystem with complementary approaches from internal, external, and commu

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McKinley, Catherine, Prem Sylvester, Benjamin Faveri, et al. Recommendations for a Global AI Auditing Framework: Summary of Standards and Features. Edited by Saiph Savage, Mona Sloam, Luis Adrián Castro-Quiroa, et al. International Panel on the Information Environment (IPIE), 2024. https://doi.org/10.61452/guyx7442.

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This Summary for Policymakers provides a high-level précis of the Synthesis Report Towards A Global AI Auditing Framework: Assessment and Recommendations. The growing integration of artificial intelligence (AI) into critical sectors of society, from healthcare to education, has the potential to support widespread social transformation and progress. However, AI systems also have the power to perpetuate biases, deepen inequalities, and cause environmental harm. Accurately evaluating the risks and benefits of an AI system requires a careful audit. Current approaches to auditing, however, rarely i

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