Artificial Intelligence-Driven Tax Compliance Architecture for Addressing Corporate Tax Avoidance

This dataset contains data from a systematic literature review and bibliometric study examining the urgency of artificial intelligence (AI) implementation by tax authorities in addressing corporate tax avoidance. The core focus spans three overlapping thematic streams: predictive risk analytics, socio-institutional trust and governance, and firm-level corporate governance tax risk. The dataset comprises 287 unique peer-reviewed journal articles indexed in Scopus over the period 2020–2025. It is intended to support analysis on how algorithmic technologies and modern information systems function as a strategic response to structural fiscal challenges.