TY - JOUR
T1 - The impact of artificial intelligence and Industry 4.0 on transforming accounting and auditing practices
AU - Abdullah, Abdulwahid Ahmad Hashed
AU - Almaqtari, Faozi A.
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/3
Y1 - 2024/3
N2 - The main aim is to investigate the impact of artificial intelligence (AI), Industry 4.0 readiness, and Technology Acceptance Model (TAM) variables on various aspects of accounting and auditing operations. To evaluate the associations between the variables, the research design employs a mediation and path approach using SMART PLS. The study employs a convenience sampling method, which is augmented with snowball sampling. The sample size was determined using various techniques, yielding a final sample of 228 respondents. The findings indicate that leveraging AI, big data analytics, cloud computing, and deep learning advancements can improve accounting and auditing practices. AI technologies assist businesses in increasing their efficiency, accuracy, and decision-making capabilities, resulting in improved financial reporting and auditing processes. The study contributes to the theoretical explanation of the influence of AI adoption in accounting and auditing practices in the context of an emerging country, Saudi Arabia. The findings of the study have practical implications for accounting and auditing practitioners, policymakers, and scholars. The findings of this study can assist businesses in efficiently leveraging AI developments to improve their accounting and auditing operations. Policymakers can use the findings to create supporting frameworks and regulations that encourage the adoption and integration of artificial intelligence in the domain. These findings contribute to the existing stock of knowledge on the use of AI in accounting and auditing, as well as providing evidence of its benefits in the context of an emerging country.
AB - The main aim is to investigate the impact of artificial intelligence (AI), Industry 4.0 readiness, and Technology Acceptance Model (TAM) variables on various aspects of accounting and auditing operations. To evaluate the associations between the variables, the research design employs a mediation and path approach using SMART PLS. The study employs a convenience sampling method, which is augmented with snowball sampling. The sample size was determined using various techniques, yielding a final sample of 228 respondents. The findings indicate that leveraging AI, big data analytics, cloud computing, and deep learning advancements can improve accounting and auditing practices. AI technologies assist businesses in increasing their efficiency, accuracy, and decision-making capabilities, resulting in improved financial reporting and auditing processes. The study contributes to the theoretical explanation of the influence of AI adoption in accounting and auditing practices in the context of an emerging country, Saudi Arabia. The findings of the study have practical implications for accounting and auditing practitioners, policymakers, and scholars. The findings of this study can assist businesses in efficiently leveraging AI developments to improve their accounting and auditing operations. Policymakers can use the findings to create supporting frameworks and regulations that encourage the adoption and integration of artificial intelligence in the domain. These findings contribute to the existing stock of knowledge on the use of AI in accounting and auditing, as well as providing evidence of its benefits in the context of an emerging country.
KW - Accounting education
KW - Accounting practices
KW - Artificial Intelligence
KW - Auditing practices
KW - Industry 4.0 readiness
KW - Technology acceptance model
UR - http://www.scopus.com/inward/record.url?scp=85184052630&partnerID=8YFLogxK
U2 - 10.1016/j.joitmc.2024.100218
DO - 10.1016/j.joitmc.2024.100218
M3 - Article
AN - SCOPUS:85184052630
SN - 2199-8531
VL - 10
JO - Journal of Open Innovation: Technology, Market, and Complexity
JF - Journal of Open Innovation: Technology, Market, and Complexity
IS - 1
M1 - 100218
ER -