Year: 2025
Type: article
Abstract: As organizations seek increased operational agility and cost-effectiveness, the integration of Artificial Intelligence (AI) with Business Process Management (BPM) is reshaping decision-making and automation. This paper explores the synergy between AI and PEGA BPM, a leading low-code platform known for its case management and decisioning capabilities. By embedding AI-driven technologies such as machine learning, natural language processing, and intelligent automation, enterprises can achieve faster processing times, improved customer personalization, and more effective risk assessment. This study examines key industry use cases and discusses architectural considerations for AI integration, including API strategies, embedded AI models, and data flow architectures. It also addresses challenges such as scalability, data privacy, and model interpretability. The paper explores future research directions, focusing on ethical AI deployment, autonomous decision systems, and hyper-automation. Using a case study approach and a systematic literature review, this research provides a comprehensive analysis of AI’s evolving role in BPM automation and its ability to drive intelligent enterprise workflows.
Author: Direesh Reddy Aunugu
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4408678566