The Impact of AI and ML Tools on the Accounting and Auditing Profession: A Survey of Student Expectations
Year: 2025
Type: conference-paper
Study design: Observational Study
Abstract: The accounting and auditing profession is undergoing a significant transformation driven by the rapid advancement and incorporation of artificial intelligence (AI) and machine learning (ML) tools. These innovative technologies have the potential to automate mundane tasks, improve data analysis capabilities, and enhance decision-making processes, fundamentally changing how accounting and auditing professionals carry out their responsibilities. While these advancements present challenges and opportunities, they also require a reevaluation of skills, knowledge, and ethical considerations for the profession to flourish in this evolving environment. This paper investigates the expectations of accounting and auditing students regarding the impact of artificial intelligence (AI) and machine learning (ML) tools on their future professions. Data was collected through a structured survey questionnaire completed by a sample of 98 students. Statistical methods, including regression analysis, were used to analyze the collected data. The results indicate that students are generally optimistic about the potential of these technologies to enhance efficiency, accuracy, and decision-making in accounting and auditing. However, they also express apprehensions about job security and the necessity for continuous learning to adapt to technological advancements.This research contributes to the literature by offering insights into the expectations of future professionals in the accounting and auditing domain and emphasizing the significance of preparing students for the evolving technological landscape. The study’s findings underline the importance of aligning educational programs with the demands of AI and ML integration to ensure the readiness of future practitioners.
Author: Almina Doko
Institution: University of Tirana
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4407604885