Authors: Sagar Gupta
Abstract: Artificial intelligence (AI) is reshaping accounting by automating routine work, elevating analytical depth, and redefining assurance and control. Drawing on developments in machine learning (ML), natural language processing (NLP), generative AI (GenAI), and robotic process automation (RPA), this paper synthesizes the current state of AI adoption across subdomains (payables, receivables, general ledger, FP&A, tax, and audit), proposes an architecture for AI-enabled controls and assurance, and presents implementation guidance, risk controls, and outcome metrics. We argue that value accrues from combinations of (1) reliable data pipelines; (2) task- and domain-specific models; (3) policy-aware automation; and (4) human-in-the-loop governance. We conclude with a staged roadmap and research agenda
DOI: http://doi.org/10.5281/zenodo.17175628
