Jun 2026· Journal of Accounting and Management Information Systems· Vol 25, pp. 166-202· 0 citations· 53 references
TL;DR
The sociomaterial lens allows us to observe that the auditor’s reconfiguration occurs dynamically and continuously, relying both on the evolution of technological capabilities (material agency) and on professionals’ engagement and adaptation (social agency).
Abstract
Research Question: What are the drivers and inhibitors of Artificial Intelligence (AI) use in auditing, and how does AI reconfigure the auditor’s role?
Motivation: The adoption of Artificial Intelligence (AI) in auditing has advanced rapidly, transforming processes, resources, and professional practices.
Idea: The analysis is grounded in sociomateriality theory and examines how the introduction of AI reconfigures the auditor’s role, posing new challenges.
Data: The study is based on a Systematic Literature Review (SLR) of 43 studies.
Tools: The sociomaterial lens is used to analyze the interaction between auditors and AI tools, considering both technological capabilities and professionals’ engagement and adaptation.
Findings: The results indicate that AI adoption in auditing is driven by efficiency, accuracy, real-time auditing, Big Data analytics and standardization. However, barriers such as resistance to change, algorithm aversion, heuristics and biases, transparency, expertise and training gaps, and complexity limit the full adoption of these technologies. This process is dynamic and ongoing: as technology evolves, organizational practices and arrangements also transform, rebalancing functions and responsibilities.
Contribution: From this perspective, the benefits of AI in auditing can be more effectively realized when organizational practices support interaction between auditors and AI tools. Therefore, the sociomaterial lens allows us to observe that the auditor’s reconfiguration occurs dynamically and continuously, relying both on the evolution of technological capabilities (material agency) and on professionals’ engagement and adaptation (social agency).
The digital transformation of the auditing profession is
accelerating as firms adopt technologies such as artificial
intelligence, blockchain, big data analytics, and robotic
process automation. While a growing body of international
literature documents the benefits and risks of these tools,
there is a lack of knowledge about auditors’ perceptions in
the Middle East. This study responds to that gap by
examining how Lebanese auditors perceive the benefits,
challenges, costs, and impacts of emerging technologies.
Building on the Technology Acceptance Model and recent
audit innovation literature, hypotheses were developed
that perceived usefulness (benefits) and ease of use
(captured through perceived costs and challenges)
influence auditors’ intention to adopt digital tools. A cross
sectional survey was distributed to Lebanese external
auditors. Eighty-four responses were analyzed using
descriptive statistics and Mann-Whitney U tests to
compare perceptions between technology users and non-
users. Results indicate that big data analytics is the most
widely adopted technology among Lebanese auditors.
Specifically, users of big data analytics reported
significantly higher median scores for perceived benefits
(e.g., improved audit quality, the ability to analyze
complete data sets, and real-time auditing) compared to
non-users. Its users also report significantly higher
benefits (e.g., improved audit quality, the ability to analyze
complete data sets, and real-time auditing) and impacts
on their work compared with non-users. Conversely,
adoption of artificial intelligence, blockchain, robotic
process automation, and metaverse tools remains limited,
and no significant differences were found between their
users and non-users.Across all technologies, auditors expressed high levels of
concern about cyber security, skills shortages, legal
uncertainties, and start up costs were perceived as high.
The findings contribute to audit technology literature by
providing evidence from a developing country context and
by extending Technology Acceptance Model to
incorporate perceived cost and risk factors. Practical
implications for regulators and practitioners include the
need for targeted training programs, supportive regulatory frameworks, and incentives to encourage investment in digital tools. Directions for future research are also
discussed.
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This paper addresses the gap in the literature regarding the adoption of Big Data Analytics (BDA) by auditors and its impact on professional skepticism (PS). It explores how auditors’ personal traits, such as prior experience, self-efficacy, and trust, influence their perceived usefulness (PU) and perceived ease of use (PEU) of BDA. Additionally, it examines how these perceptions affect their behavioral intentions (BI) to adopt BDA tools, whether this leads to actual usage (AU), and subsequently investigates whether the AU of BDA impacts PS. A questionnaire was prepared and distributed to 94 external auditors from the Big Four auditing firms in Palestine (86% response rate) by adopting the census method. The findings indicate that certain auditors’ characteristics positively influence perceptions of BDA’s usefulness and ease of use, subsequently affecting adoption intentions and actual adoption. However, not all auditors’ characteristics show this positive influence. Furthermore, the AU of BDA is found to significantly impact PS, suggesting that BDA tools could enhance audit quality. The study’s results emphasize the importance of keeping PS strong as technology evolves. These findings are essential for audit firms looking to use BDA to improve audit quality.
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