Design and implementation of generative Artificial Intelligence–driven automation for enterprise customer relationship management decision support systems

The rapid growth of generative artificial intelligence (GenAI) is reshaping enterprise decision support systems, especially in customer relationship management (CRM). Many organizations now use intelligent automation to improve customer interaction analysis, predictive modeling, and managerial decision-making. This study proposes a Generative AI-Driven Automation Framework for CRM Decision Support Systems (GAI-CRM DSS) that integrates large language models, real-time analytics, and enterprise data ecosystems within a unified architecture. The framework supports automated customer insight generation, sentiment analysis, recommendation functions, and adaptive decision support. It also incorporates cloud-based microservices, data pipelines, and explainable AI components to support scalability, transparency, and governance requirements. The framework is examined through simulated enterprise use cases, including sales forecasting, customer segmentation, and customer support automation. The findings indicate improvements in decision accuracy, operational efficiency, and service responsiveness. The proposed framework offers a practical model for organizations seeking to modernize CRM decision support through generative AI technologies.