Robotic Process Automation

The growing emphasis on digital transformation in organizations has positioned Robotic Process Automation (RPA) as a practical solution for improving efficiency in routine financial and accounting operations. Unlike artificial intelligence, which relies on learning and prediction, RPA is a rule-based system designed to replicate human actions in digital environments such as data entry, reconciliation, and compliance reporting. While its potential is widely acknowledged, managers often lack a structured method to evaluate which accounting tasks are most suitable for automation and how to ensure successful implementation. This paper develops a managerial framework for RPA adoption in accounting that integrates five decision criteria—transaction volume, repetition, complexity, compliance risk, and business value—to assess task suitability. A pilot-to-scale governance model is also proposed, outlining four stages: selection, pilot implementation, performance measurement, and scaling. An illustrative case of bank reconciliation demonstrates how the framework can reduce manual effort, minimize errors, and accelerate reporting cycles. The contribution of this study lies in offering a simple, actionable tool for managers to navigate RPA adoption without requiring deep technical or accounting expertise. By linking digital innovation to managerial decision-making, the framework provides both academic and practical value, supporting organizations in initiating low-risk automation initiatives and building capacity for broader digital transformation.