Sources data available from:

https://www.dropbox.com/scl/fo/wctqkn3sxd2ygxb4qdtez/AJvz9Gjh2vNWluZxdrZYxhw?rlkey=rr72gwbx9brzo8bkdxwkn4h0y&st=nscsgzb3&dl=0

  1. Bracci, Enrico. ‘The Loopholes of Algorithmic Public Services: An “Intelligent” Accountability Research Agenda’. Accounting, Auditing & Accountability Journal 36, no. 2 (27 March 2023): 739–63. https://doi.org/10.1108/AAAJ-06-2022-5856.

  2. Commerford, Benjamin P., Sean A. Dennis, Jennifer R. Joe, and Jenny W. Ulla. ‘Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence’. Journal of Accounting Research 60, no. 1 (March 2022): 171–201. https://doi.org/10.1111/1475-679X.12407.

  3. De Villiers, Charl, John Dumay, and Warren Maroun. ‘Qualitative Accounting Research: Dispelling Myths and Developing a New Research Agenda’. Accounting & Finance 59, no. 3 (September 2019): 1459–87. https://doi.org/10.1111/acfi.12487.

  4. Di Tullio, Patrizia, Matteo La Torre, Michele Antonio Rea, James Guthrie, and John Dumay. ‘Beyond the Planetary Boundaries: Exploring Pluralistic Accountability in the New Space Age’. Accounting, Auditing & Accountability Journal 37, no. 5 (2 July 2024): 1283–1311. https://doi.org/10.1108/AAAJ-08-2022-6003.

  5. Eilifsen, Aasmund, Finn Kinserdal, William F. Messier, and Thomas E. McKee. ‘An Exploratory Study into the Use of Audit Data Analytics on Audit Engagements’. Accounting Horizons 34, no. 4 (1 December 2020): 75–103. https://doi.org/10.2308/HORIZONS-19-121.

  6. Gepp, Adrian, Martina K. Linnenluecke, Terrence J. O’Neill, and Tom Smith. ‘Big Data Techniques in Auditing Research and Practice: Current Trends and Future Opportunities’. Journal of Accounting Literature 40, no. 1 (30 June 2018): 102–15. https://doi.org/10.1016/j.acclit.2017.05.003.

  7. Kokina, Julia, and Thomas H. Davenport. ‘The Emergence of Artificial Intelligence: How Automation Is Changing Auditing’. Journal of Emerging Technologies in Accounting 14, no. 1 (1 March 2017): 115–22. https://doi.org/10.2308/jeta-51730.

  8. Landers, Richard N., and Tara S. Behrend. ‘Auditing the AI Auditors: A Framework for Evaluating Fairness and Bias in High Stakes AI Predictive Models.’ American Psychologist 78, no. 1 (January 2023): 36–49. https://doi.org/10.1037/amp0000972.

  9. Lombardi, Rosa, Charl De Villiers, Nicola Moscariello, and Michele Pizzo. ‘The Disruption of Blockchain in Auditing – a Systematic Literature Review and an Agenda for Future Research’. Accounting, Auditing & Accountability Journal 35, no. 7 (22 August 2022): 1534–65. https://doi.org/10.1108/AAAJ-10-2020-4992.

  10. Mohamed Shaffril, Hayrol Azril, Samsul Farid Samsuddin, and Asnarulkhadi Abu Samah. ‘The ABC of Systematic Literature Review: The Basic Methodological Guidance for Beginners’. Quality & Quantity 55, no. 4 (August 2021): 1319–46. https://doi.org/10.1007/s11135-020-01059-6.

  11. Salijeni, George, Anna Samsonova-Taddei, and Stuart Turley. ‘Understanding How Big Data Technologies Reconfigure the Nature and Organization of Financial Statement Audits: A Sociomaterial Analysis’. European Accounting Review 30, no. 3 (27 May 2021): 531–55. https://doi.org/10.1080/09638180.2021.1882320.

  12. Staszkiewicz, Piotr, Jarosław Horobiowski, Anna Szelągowska, and Agnieszka Maryla Strzelecka. ‘Artificial Intelligence Legal Personality and Accountability: Auditors’ Accounts of Capabilities and Challenges for Instrument Boundary’. Meditari Accountancy Research 32, no. 7 (25 June 2024): 120–46. https://doi.org/10.1108/MEDAR-10-2023-2204.

  13. Tiron-Tudor, Adriana, and Delia Deliu. ‘Reflections on the Human-Algorithm Complex Duality Perspectives in the Auditing Process’, n.d.