AI-DRIVEN SMART CONTRACTS FOR AUTOMATED COMPLIANCE AND GOVERNANCE IN BLOCKCHAIN-BASED PUBLIC-SECTOR PLATFORMS
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Abstract
Public sector digital frameworks are increasingly combining distributed ledgers and programmable intelligent contracts to make administrative transactions verifiable, traceable and automatically executable. But traditional intelligent contracts are rigid: they can enforce pre-defined logic but cannot interpret ambiguous regulations, identify changing risk or explain why a transaction should be escalated. This disadvantage can be mitigated to some degree by using artificial intelligence for assisting with the interpretation of regulatory text, anomaly detection, predictive risk scoring, document classification, and adaptive workflow control. This review offers an in-depth analysis of the potential for AI-enabled smart contract technology to automate compliance and governance in blockchain-based public-sector platforms while maintaining legality, accountability, privacy, security and administrative discretion. The integrative review design was developed by synthesising peer-reviewed work published between 2020 and 2025, mainly through discovery pathways in Scopus, Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and Google Scholar. The review describes the search logic, eligibility criteria, quality assessment and thematic synthesis process instead of invented screening numbers.
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Sathya Narayanan Lakshmi Kantham (2026); AI-DRIVEN SMART CONTRACTS FOR AUTOMATED COMPLIANCE AND GOVERNANCE IN BLOCKCHAIN-BASED PUBLIC-SECTOR PLATFORMS, International Journal of Advanced Research (IJAR), 14 (09), 1247-1257, ISSN 2320-5407.
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