Title: Cognitive Automation of SAP Business Workflows Using Deep Reinforcement Learning Agents

Abstract: SAP S/4HANA and similar Enterprise Resource Planning (ERP) systems are the technological core of contemporary companies. However, most of their vital business processes are still manually set up, governed by rules, and inflexible in nature. This paper presents a cognitive automation framework using Deep Reinforcement Learning (DRL) agents for the execution, adaptation, and optimization of business workflows. Unlike traditional scripting or robotic process automation (RPA), the agents powered by DRL improve decision making across modules like Financial Accounting, Materials Management, and Sales and Distribution through continuous interaction with the SAP environment. The framework facilitates policy convergence for automation of high-impact scenarios such as invoice processing, purchase requisition approval, and delivery confirmation by modeling SAP states, actions, and rewards. In a simulated SAP testbed, the agents showed up to 35% improvement in time to completion of workflows, 42% reduction in transactional errors, and strong adaptiveness to new variants of processes. This research is not only a step forward towards incorporating cognitive AI into ERP systems, but also provides a new scalable and modular blueprint for agile intelligent enterprise automation.

Keywords: Cognitive ERP Automation, Deep Reinforcement Learning Agents, SAP Workflow Optimization