Data Science Techniques in Pega – Optimizing Business Process Automation

Abstract

Artificial Intelligence (AI) and Data Science techniques are revolutionizing
Business Process Automation (BPA) by enabling intelligent, data-driven decision-
making. Pega Systems, a leading low-code business process management platform,
integrates AI-driven predictive analytics, process mining, reinforcement learning
(RL), and natural language processing (NLP) to optimize workflows, improve
efficiency, and enhance customer engagement. This research presents a
comprehensive AI-driven BPA framework leveraging machine learning models for
workflow prediction, process mining for compliance, RL for dynamic decision
optimization, and NLP for automated case management. The proposed approach
was evaluated using real-world enterprise workflow datasets, demonstrating
significant improvements in workflow compliance (from 78% to 94%), process
efficiency (25% increase), and automation effectiveness (60% reduction in manual
efforts). The results confirm that AI-integrated BPA in Pega Systems significantly
enhances decision automation, operational efficiency, and business agility.