Empowering Rules Engines: AI and ML Enhancements in BRMS for Agile Business Strategies

Naga Ramesh Palakurti

Empowering Rules Engines: AI and ML Enhancements in BRMS for Agile Business Strategies

Authors

Naga Ramesh Palakurti

Abstract

This research paper explores the dynamic integration of artificial intelligence (AI) and machine learning (ML) to enhance Business Rules Management Systems (BRMS) for the facilitation of agile business strategies. In the evolving landscape of digital enterprises, the demand for adaptive and responsive decision-making processes is paramount. The abstract investigates the symbiotic relationship between AI, ML, and BRMS, elucidating their combined potential to empower organizations in crafting agile and resilient business strategies. The study delves into the mechanisms by which AI and ML augment traditional BRMS, offering predictive insights, optimizing decision rules, and fostering real-time adaptability. Through a comprehensive analysis, the research aims to provide valuable insights into the transformative capabilities of this integrated approach, shedding light on its implications for business agility, competitiveness, and strategic innovation

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Empowering Rules Engines: AI and ML Enhancements in BRMS for Agile Business Strategies