Artificial Intelligence in Accounting: The Perception of Accounting Professionals

Ana Filipa Roque (), Maria Céu Alves () and Guilherme Ramos ()
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Ana Filipa Roque: Polytechnic University of Coimbra, Coimbra Business School
Maria Céu Alves: University of Beira Interior, Department of Management and Economics
Guilherme Ramos: University of Beira Interior, Department of Management and Economics

A chapter in Eurasian Business and Economics Perspectives, 2026, pp 145-164 from Springer

Abstract: Abstract Integrating Artificial Intelligence (AI) in Accounting has driven significant advances, reshaping practices and professional roles. Literature increasingly emphasizes a hybrid approach, where accountants use AI tools to analyze and interpret data, enhancing their decision-making capabilities. This study examines the implementation of AI in accounting and the perceptions of professionals, thereby contributing to the knowledge base on the development of AI. The study begins with a literature review to assess the presence of AI in accounting, followed by an empirical study conducted with Portuguese professionals. An interview guide was designed to verify whether findings from the literature align with real-world experiences. Results highlight the benefits of AI in accounting, such as increased precision, efficiency, and strategic insights. Proper AI implementation enhances multiple company areas and adds value to the profession. Continuous training is crucial for professionals to adapt to technological changes. However, challenges exist. Difficulty in recruiting interviewees and limited academic studies hinder deeper exploration. This research seeks to address this gap. Future research should examine AI’s role in specific accounting tasks, its impact on higher education, and how security and privacy challenges will evolve in light of the vast amounts of data being processed, which will influence accountants’ responsibilities.

Keywords: Accounting; Artificial intelligence; ChatGPT; Portugal (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-10967-5_8

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