Reflections on the human-algorithm complex duality perspectives in the auditing process

Purpose - Algorithms, artificial intelligence (AI), machines, and all emerging digital technologies disrupt traditional auditing, raising many questions and debates. One of the central issues of this debate is the human-algorithms complex duality, which focuses on this investigation. This study aims to investigate the algorithms’ penetration in auditing activities, with a specific focus of a future scenario on the human-algorithms interaction in performing audits as intelligent teams. Design/methodology/approach - The research uses a qualitative reflexive thematic analysis, taking into consideration the academic literature, as well as professional reports and websites of the “Big Four” audit firms and internationally recognized accounting bodies. Findings - The results debate the complex duality between algorithms and human-based actions in the institutional settings of auditing activities by highlighting the actual stage of algorithms, machines and AI emergence in audit and providing real-life examples of their use in the audit. Furthermore, they emphasize the strengths and weaknesses of algorithms compared to human beings. Based on the results, a discussion on the human-algorithms interaction from the lens of the Human-in-the-Loop (HITL) approach concludes that the Auditor-Governing-the-Loop may be a possible scenario for the future of the auditing profession. Research limitations/implications - This study is exploratory, investigating academia and practitioners’ written debates, analyzes and reports, limiting its applicability. Nonetheless, the paper adds to the ongoing discussion on emerging technologies and auditing research. Finally, the authors address some potential biases associated with the extended use of algorithms and discuss future research implications. Future research should empirically test how the human-algorithms tandem is working and how AI and other emerging technologies will affect auditing activities and the auditing profession. Practical implications - The study provides valuable insights for audit firms, auditors, professional organizations and standard-setters, and regulators revealing the implication of algorithms’ penetration in auditing activities from the human-algorithms complex duality perspective. Moreover, the academic education and research implications are highlighted, in terms of updating the educational curriculum by including the new technologies issues, as well as the need for further research investigations concerning the human-algorithms interactions issues as, for example, trust, legal restrictions, ethical concerns, security and responsibility. Originality/value - The research uses HITL as a novel paradigm for responsible AI development in auditing. The study points to the strategic value of a HITL pattern for organizational reflexivity that, according to the study, ensures that the algorithm’s output meets the audit organization’s requirements and changes in the environment.