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Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking

Author

Listed:
  • Othmar Manfred Lehner
  • Kim Ittonen
  • Hanna Silvola
  • Eva Ström
  • Alena Wührleitner

Abstract

Purpose - This paper aims to identify ethical challenges of using artificial intelligence (AI)-based accounting systems for decision-making and discusses its findings based on Rest's four-component model of antecedents for ethical decision-making. This study derives implications for accounting and auditing scholars and practitioners. Design/methodology/approach - This research is rooted in the hermeneutics tradition of interpretative accounting research, in which the reader and the texts engage in a form of dialogue. To substantiate this dialogue, the authors conduct a theoretically informed, narrative (semi-systematic) literature review spanning the years 2015–2020. This review's narrative is driven by the depicted contexts and the accounting/auditing practices found in selected articles are used as sample instead of the research or methods. Findings - In the thematic coding of the selected papers the authors identify five major ethical challenges of AI-based decision-making in accounting: objectivity, privacy, transparency, accountability and trustworthiness. Using Rest's component model of antecedents for ethical decision-making as a stable framework for our structure, the authors critically discuss the challenges and their relevance for a future human–machine collaboration within varying agency between humans and AI. Originality/value - This paper contributes to the literature on accounting as a subjectivising as well as mediating practice in a socio-material context. It does so by providing a solid base of arguments that AI alone, despite its enabling and mediating role in accounting, cannot make ethical accounting decisions because it lacks the necessary preconditions in terms of Rest's model of antecedents. What is more, as AI is bound to pre-set goals and subjected to human made conditions despite its autonomous learning and adaptive practices, it lacks true agency. As a consequence, accountability needs to be shared between humans and AI. The authors suggest that related governance as well as internal and external auditing processes need to be adapted in terms of skills and awareness to ensure an ethical AI-based decision-making.

Suggested Citation

  • Othmar Manfred Lehner & Kim Ittonen & Hanna Silvola & Eva Ström & Alena Wührleitner, 2022. "Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 35(9), pages 109-135, June.
    • Handle: RePEc:eme:aaajpp:aaaj-09-2020-4934
    DOI: 10.1108/AAAJ-09-2020-4934
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    Citations

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    Cited by:

    1. Isip Adrian, 2025. "The Impact Regarding the Use of Robotic Process Automation and Artificial Intelligence in Accounting Services Industry," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 122-137.
    2. Ndaka, Angella & Lassou, Philippe J.C. & Kan, Konan Anderson Seny & Fosso-Wamba, Samuel, 2024. "Toward response-able AI: A decolonial perspective to AI-enabled accounting systems in Africa," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 99(C).
    3. Favourate y Mpofu, 2023. "The application of Artificial Intelligence in external auditing and its implications on audit quality? A review of the ongoing debates," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 12(9), pages 496-512, December.
    4. repec:bcp:journl:v:9:y:2025:i:22:p:484-491 is not listed on IDEAS
    5. Mihaela PANAIT (ION) & Marilena-Roxana ZUCA & Aura Oana MUSTÄ‚ÈšEA & Victor MUNTEANU, 2025. "Challenges, Opportunities And Implications Regarding The Integration Of Artificial Intelligence In Audit Processes," Journal of Information Systems & Operations Management, Romanian-American University, vol. 19(1), pages 138-161, May.
    6. Sinziana-Maria Rindasu & Ioan Dan Topor & Liliana Ionescu-Feleaga, 2023. "The Evolution of Management Accountants' Digital Skills in Industry 4.0: A Qualitative Approach," Oblik i finansi, Institute of Accounting and Finance, issue 1, pages 38-48, March.
    7. Torroba, Macarena & Sánchez, José Ramón & López, Lidia & Callejón, Ángela, 2025. "Investigating the impacting factors for the audit professionals to adopt data analysis and artificial intelligence: Empirical evidence for Spain," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
    8. Elsayed, Nader, 2025. "Strategic AI disclosures and legitimacy: Impression management in UK FTSE100 annual reports," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
    9. Queen MPOFU & Odette SWART, 2024. "Revolutionising Accounting Education through AI: Is Africa Ready for personalised learning, improved Assessments, and skills development?," Social Sciences and Education Research Review, Department of Communication, Journalism and Education Sciences, University of Craiova, vol. 11(2), pages 171-179, December.
    10. Luo, Haotian & Yu, Jinlei & Mu, Tong & Zhou, Peng, 2025. "Spillover effects of enterprise digital transformation on supply chain carbon emissions: Evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 75(C), pages 606-617.
    11. Alaskar, Mohammad Zaid & Kim, Ja Ryong & Nguyen, Tam Huy & Rafique, Muhammad, 2025. "Balancing performance and ethics: Navigating visual recognition technology adoption in the auditing industry," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 59(C).
    12. Lombardi, Danielle R. & Kim, Meehyun & Sipior, Janice C. & Vasarhelyi, Miklos A., 2025. "The increased role of advanced technology and automation in audit: A delphi study," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
    13. Yixuan Peng & Sayed Fayaz Ahmad & Ahmad Y. A. Bani Ahmad & Mustafa S. Al Shaikh & Mohammad Khalaf Daoud & Fuad Mohammed Hussein Alhamdi, 2023. "Riding the Waves of Artificial Intelligence in Advancing Accounting and Its Implications for Sustainable Development Goals," Sustainability, MDPI, vol. 15(19), pages 1-12, September.
    14. Murphy, Brid & Feeney, Orla & Rosati, Pierangelo & Lynn, Theo, 2024. "Exploring accounting and AI using topic modelling," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).
    15. Fotoh, Lazarus Elad & Mugwira, Tatenda, 2025. "Exploring Large Language Models in external audits: Implications and ethical considerations," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
    16. Grosu, Veronica & Cosmulese, Cristina Gabriela & Socoliuc, Marian & Ciubotariu, Marius-Sorin & Mihaila, Svetlana, 2023. "Testing accountants' perceptions of the digitization of the profession and profiling the future professional," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    17. Ram, Jiwat, 2025. "Moral decision-making in AI: A comprehensive review and recommendations," Technological Forecasting and Social Change, Elsevier, vol. 217(C).
    18. Meryem Ayad & Said El Mezouari, 2022. "Research on the implication of artificial intelligence in accounting subfields: current research trends from bibliometric analysis, and research directions," Post-Print hal-05138659, HAL.
    19. Yuna Lee & Sang-Soo Lee, 2025. "Exploring the Conceptual Model and Instructional Design Principles of Intelligent Problem-Solving Learning," Sustainability, MDPI, vol. 17(17), pages 1-33, August.
    20. Adrian GROȘANU & Melinda-Timea FÜLÖP & Nicolae MĂGDAȘ, 2024. "Ethical Dilemmas in Digital Accounting: A Comprehensive Literature Review," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 5(4), pages 56-67, April.

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