Exploring the Role of AI-Orchestrated Workflow Automation in Cloud CRM to Enhance Operational Efficiency Through Intelligent Task Management

Jaseem Pookandy

Authors

Jaseem Pookandy Principal Software Engineer, Carmax, USA Author

Keywords:

AI-driven automation, workflow automation, cloud CRM, task management, operational efficiency, AI in CRM, resource allocation, real-time performance monitoring

Abstract

As businesses increasingly rely on digital solutions to streamline operations, the integration of artificial intelligence (AI) in cloud-based Customer Relationship Management (CRM) systems is transforming task management and operational workflows. This research paper explores the role of AI-orchestrated workflow automation in cloud-based CRM systems and its impact on enhancing operational efficiency through intelligent task management. By analyzing both qualitative insights and quantitative performance data, the study demonstrates how AI-driven automation improves task completion rates, reduces task delays, and optimizes resource allocation within CRM workflows. The findings reveal a significant increase in efficiency, driven by AI’s ability to automate routine tasks and provide real-time performance monitoring. The research also compares the results with existing literature, noting key consistencies and identifying areas for future exploration. While the study presents promising results, it acknowledges limitations related to sample diversity and the long-term implications of AI adoption.

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