Enhancing Tax Consultants' Performance and Productivity through Digital Literacy and Artificial Intelligence: A Systematic Literature Review

Abstract

This literature study discusses the challenges and opportunities for applying artificial Intelligence (AI) to improve the performance and productivity of tax consultants, particularly in terms of work efficiency, analysis accuracy, and professional productivity management. This study aims to comprehensively examine the role and contribution of AI to the performance and productivity of tax consultants through a Systematic Literature Review (SLR) and bibliometric analysis. Research data was obtained from articles indexed in the Scopus, SINTA, and Google Scholar databases with a publication range of 2021–2025. Of the total 107 articles identified, 42 articles were selected for further analysis based on the inclusion criteria. A bibliometric analysis was conducted using VOSviewer to map research patterns through co-authorship, co-occurrence, and citation analysis. The study's results show that AI plays a significant role in improving work efficiency, reducing the risk of analytical errors, and supporting data-driven decision-making in tax consulting practice. However, the success of AI adoption is greatly influenced by tax consultants' digital literacy. Consultants with good digital literacy are better able to understand, integrate, and make optimal use of AI in professional work processes. Thus, digital literacy is a key factor that enhances AI's contribution to improving the performance and productivity of tax consultants. This study is expected to serve as a relevant bibliographic reference for future research in taxation, technology, and professional services.

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