Tax Transformation through Artificial Intelligence: A Systematic Review of Generational Preference Differences and their Impact on Tax Compliance - Hakam, Lazuardi Imani; Kurniawati, Susanti; Akram, Fathin Mufid; Salim, Dhea Ramadhani; Fuadi, Siti Sarah (Politeknik Keuangan Negara STAN, 2024)
This study aims to analyze the impact of AI adoption on tax compliance with a focus on generational differences. Then, it provides scientific evidence from the perspective of Generation, X, Y, and Z regarding the impact of AI on tax compliance. This research departs from the concern that studies on Artificial Intelligence implications in the field of taxation generally only focus on technical aspects and its impact on tax authorities, but do not really explore how AI affects taxpayer behavior, especially generational differences in tax compliance. This research uses a systematic review method with the PRISMA framework. The purpose of this review is to identify, analyze, and synthesize peer-reviewed journal articles from the Scopus database that address the role of AI, tax compliance, and generational differences in technology adoption. Data from the selected studies were synthesized using a thematic analysis approach, a method that involves identifying themes and patterns that recur across studies. Based on the results, AI significantly improves the efficiency of tax administration by automating complex processes. The younger generation sees AI as a way to improve financial and taxation processes, while the older generation is slower to adopt this technology due to concerns about data security and lack of skills in digital platforms. AI offers great prospects for improving tax compliance and administration, but its success depends on addressing the age gap in technology adoption. Policymakers should tailor their approach to the specific needs of each age group, providing incentives and convenience for young users and emphasizing trust and assistance for older users.