Artificial Intelligence Adoption in Tax Administration and Its Impact on Corporate Tax Compliance in Emerging and Advanced Economies
Artificial Intelligence Adoption in Tax Administration and Its Impact on Corporate Tax Compliance in Emerging and Advanced Economies

Summary/Abstract: This study examined the impact of Artificial Intelligence Adoption in Tax Administration and Its Impact on Corporate Tax Compliance in Emerging and Advanced Economies, with emphasis on the E-Government Development Index (EGDI), electronic tax filing adoption (e-filing rate), and Government AI Readiness (GAIR). A quantitative ex post facto research design was employed, relying on secondary data drawn from credible international institutions such as the United Nations Department of Economic and Social Affairs (UN-DESA), World Bank, International Monetary Fund (IMF), Organisation for Economic Co-operation and Development (OECD), and national tax agencies, covering the period 2013–2024. A purposive sample of twelve countries was selected to capture technological and institutional diversity: six advanced economies (Estonia, Singapore, United States, Australia, Denmark, and South Korea) and six emerging economies (Rwanda, Nigeria, Brazil, Mexico, Malaysia, and Chile). The data were analyzed using descriptive statistics, the Hausman specification test, Arellano-Bond dynamic panel GMM estimation, variance inflation factor diagnostics, and heteroskedasticity and autocorrelation tests. The results revealed that EGDI (β = 0.102, p = 0.014), e-filing adoption (β = 0.086, p = 0.026), and GAIR (β = 0.079, p = 0.031) each had a statistically significant and positive effect on corporate tax compliance. Additionally, digital infrastructure (β = 0.097, p = 0.019), institutional quality (β = 0.073, p = 0.037), and economic development (β = 0.061, p = 0.044) further strengthened compliance outcomes. The lagged tax compliance index (β = 0.342, p = 0.000) indicated strong persistence of compliance behavior over time. Diagnostic tests confirmed the absence of second-order autocorrelation and the validity of instruments used in the GMM model. The findings demonstrated that advanced economies benefited from sustaining innovation in digital tax systems, while emerging economies, particularly Rwanda and Nigeria, showed potential for digital leapfrogging to rapidly close compliance gaps. This underscores the importance of systemic digital readiness in improving tax administration effectiveness globally.

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