Audit Data Analytics, the Transformation within the Audit Profession: Perspectives from the Kingdom of Saudi Arabia

Emerging and advanced audit data analytics (ADA) technologies such as big data analytics (BDA) and artificial intelligence (AI) algorithms that can analyse vast amounts of structured, semi-structured, and unstructured data are changing the auditing industry's practices, processes, and evidence collection processes. This research will investigate factors that encouraged or discouraged Saudi audit firms from investing capital in emerging and advanced (ADA) technologies such as BDA and AI tools. Also examined here are new forms of audit evidence generated by these emerging and advanced technologies and factors that facilitate or impede the collection of such audit evidence. Furthermore, this study will explore the differences between listed and unlisted audit clients regarding the audit processes when advanced or emerging technologies are deployed. Diffusion of innovation (DOI) theory, technological-organisational-environmental (TOE) framework, and socio-technical (ST) theory will serve as the basis for the theoretical framework for this study. The study will use two methodologies to collect data: firstly, conducting semi-structured interviews with participants who have knowledge and experience of emerging and advanced ADA technologies for auditing, and secondly, reviews of the documentary data sources generated by audit firms on this topic. In this study, empirical findings from Saudi Arabia will be presented on the transformation occurring in the audit profession where emerging and advanced ADA technologies are being used. This study presents four contributions. The present study is one of the first to reveal capital investment decisions in emerging and advanced ADA technologies since it provides empirical knowledge aimed at enhancing academic perceptions in this area. It is also one of the first studies to provide empirical evidence about the new forms of audit evidence and the differences in audit processes between listed and unlisted clients when using ADA tools. For practical contribution, this study provides a comprehensive capital investment decision-making model in ADA technologies that consists of three pillars (i.e., technological, organisational, and external environmental), which allows audit firms to make informed capital investment decisions in emerging and advanced ADA technologies. In terms of theoretical contributions, this study is among the first to combine diffusion of innovation (DOI) with technological-organisational-environmental (TOE) theories to interpret findings about RQ1 and RQ2. This study is the first to utilize ST system theory to investigate the phenomenon of RQ3 since this topic has not been addressed previously. As a methodological contribution, this study utilized two qualitative data collection methods (i.e., semi-structured interviews and documentary sources) in conjunction with interpretivism philosophy in order to support and strengthen its findings. The findings reveal that KSA audit firms have many reasons (i.e., technological, organisational, and external environmental) for investing or not investing in ADA technologies. Technological factors are relative advantages, compatibility, complexity, trialability, observability, uncertainty vs. certainty, and trust in such technologies. Several organisational factors lead KSA audit firms to invest in ADA technologies: improvements of their operations, leadership support, the readiness of KSA audit firms, and technological competencies of auditors and other relevant employees. External environmental factors that encourage or discourage KSA audit firms from investing in such technologies are the country’s regulations and regulators, international auditing standards, competitive pressures, and trading partners' or clients’ requirements. It is not necessary for each audit firm to consider all these factors before deciding to invest or delay investment in audit technologies. However, it is more beneficial that KSA audit firms consider all these factors before deciding to invest in modern audit techniques, as they can look at matters from many angles and in detail, which gives them a better opportunity to make informed decisions. The findings about the new forms of audit evidence have been interpreted based on DOI and TOE theories, and they KSA audit firms did generate new forms of audit evidence by analysing the entire population of clients' data using AI and BDA, Radio Frequency Identification (RFID), drones, and sensors. The technical-based factors that lead KSA audit firms to generate new forms of audit evidence are relative advantages, compatibility, complexity, and simplicity. Organisational aspects that simplify the generation of new forms of audit evidence are leadership commitment and support and seeking to improve how audit firms operate with reference to external auditing practices. Finally, collecting new forms of audit evidence has been influenced significantly by external environmental factors such as government regulations and audit standards, audited clients, and competitive pressures. The findings about the differences in audit processes between listed and unlisted audit clients to collect new forms of evidence using modern technologies are driven by the six elements that comprise the ST system framework. These six elements drive four factors that establish the differences in audit processes and the use of ADA technologies between listed and unlisted clients: risk levels, regulations, accounting standards, and differences in the quality and quantity of the data provided by each client category (i.e., listed, or unlisted).