This paper explores the multifaceted impact of Artificial Intelligence (AI) on accounting practices, addressing key dimensions of advancements, challenges, and opportunities. The definition of AI in accounting is established, tracing its historical context. Advancements are detailed, encompassing the automation of routine tasks, predictive analytics, and fraud detection. Challenges in imple…
The accelerated progress of Artificial Intelligence (AI) within the accounting field has resulted in a heightened use of this technology in international enterprises, therefore generating noteworthy ethical concerns. This research investigates the ethical implications that arise from the use of AI in accounting practices, focusing on international corporations operating in Jordan. The object…
The use of artificial intelligence (AI) is becoming more prevalent across industries such as healthcare, finance, and transportation. Artificial intelligence is based on the analysis of large datasets and requires a continuous supply of high-quality data. However, using data for AI is not without challenges. This paper comprehensively reviews and critically examines the challenges of using d…
This is a review work in the area of application of Artificial Intelligence (AI) in Accounting and Auditing. A semi-systematic or narrative review approach was employed in analyzing relevant published books and journals. Faced with the challenges of disruptive technologies brought forth by the Industry 4.0, the accounting and auditing discipline is required to undergo a metamorpho- sis i…
Can predictive AI models be successfully deployed to help investors process complex financial information? We answer this question by examining the usefulness of ChatGPT generated sentiment and complexity scores for a sample of UK annual reports. We document that both measures contain economically significant value-relevant information as captured by their association with (i) price reactio…
We examine the impact of social media sentiment on the informational efficiency of financial markets. Specifically, we explore the relationship between sentiment extracted from Twitter posts and two commonly used measures of efficiency: return autocorrelation and variance ratio. Our findings reveal that higher sentiment leads to higher return autocorrelation and variance ratio the following…
Unstructured text contains valuable information for a range of enterprise applications and informed decision making. Text analytics is used to extract valuable insights from unstructured big data. Among the most significant challenges of text analytics, quality and usability are critical in affecting the outcome of the analytical process. The enhancement in usability is important for the exp…