Pavan Kumar Rajagopal Prakashkumar
Pavan Kumar Rajagopal Prakashkumar
Sr. Principal Consultant, Apps Associates LLC
Aiding Finance and Account activities leveraging Agentic AI
Financial and accounting operations remain burdened by manual, rule-based processes for reconciliation, invoice processing, compliance checks, and reporting. This paper examines Agentic AI systems, autonomous, goal-directed AI agents capable of planning, tool use, and multi-step decision-making, as a mechanism for automating these workflows beyond traditional RPA and rule engines. Unlike static automation, agentic architectures can interpret unstructured financial data, adapt to exceptions, invoke APIs and enterprise systems, and execute multi-stage tasks such as accounts payable/receivable management, fraud detection, audit trail generation, and regulatory reporting with minimal human intervention. The study outlines core architectural components: perception modules for data ingestion, reasoning layers for decision logic, memory for contextual continuity, and action modules for system integration. Key benefits identified include reduced processing time, improved accuracy, and scalability across high-volume transactions. Challenges addressed include model explainability, auditability, data security, and regulatory compliance. The paper concludes with a framework for responsible deployment of agentic AI in finance and accounting functions.