International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Human-AI Symbiosis in Business Process Automation: A Framework for Maximizing Operational Efficiency

Author(s) Ranadheer Suram
Country United States
Abstract This article examines the strategic integration of human expertise and artificial intelligence (AI) in business workflow automation, focusing on maximizing operational efficiency through collaborative approaches. The article investigates how organizations can effectively balance human cognitive capabilities with AI-driven automation to optimize business processes while maintaining quality and
operational excellence. This article presents a framework for implementing human-AI collaboration through systematic analysis that encompasses data-driven process optimization, customer service enhancement, and continuous feedback integration. The article identifies key factors contributing to
successful human-AI collaboration, including strategic training programs, feedback loop mechanisms, and balanced workload distribution between human agents and AI systems. Findings indicate that organizations implementing well-structured human-AI collaborative models demonstrate enhanced workflow efficiency, improved customer service delivery, and increased team productivity. This article contributes to the growing knowledge of human-AI collaboration in business operations. It provides practical insights for organizations seeking to optimize workflow processes through intelligent automation while leveraging human expertise.
Keywords Human-AI Collaboration, Workflow Automation, Business Process Optimization, Feedback Integration Systems, Operational Efficiency.
Field Computer
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-01-10
Cite This Human-AI Symbiosis in Business Process Automation: A Framework for Maximizing Operational Efficiency - Ranadheer Suram - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.33983
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.33983
Short DOI https://doi.org/g82hkc
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