Revolutionizing Customer Service: Adaptive Workflow Automation for Case Management

Authors

  • Nishanth Kumar Reddy Kesavareddi Murray State University

DOI:

https://doi.org/10.47941/ijce.2941

Keywords:

Adaptive Workflow Automation, Case Management Optimization, AI-Driven Routing, Omnichannel Integration, Predictive Analytics

Abstract

This comprehensive technical article examines the transformative potential of adaptive workflow automation in modernizing case management systems for customer service operations. The framework integrates Microsoft Power Platform capabilities with artificial intelligence to address persistent challenges, including lengthy resolution times, inconsistent protocol application, and fragmented multichannel experiences. By implementing intelligent routing algorithms, automated escalation protocols, predictive analytics, and omnichannel integration, organizations can significantly enhance operational efficiency while simultaneously improving customer satisfaction. The solution analyzes multiple dimensions, including ticket severity, SLA parameters, agent workloads, and historical performance to optimize case assignments and proactively identify at-risk cases before service failures occur. The article explores implementation benefits spanning resolution efficiency, compliance adherence, and employee satisfaction while addressing critical architectural considerations for successful deployment. Through phased implementation approaches that progressively expand capabilities, organizations can establish adaptable service infrastructures capable of evolving with changing customer expectations and technological capabilities.

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References

Sorin Gavrila et al., "The impact of automation and optimization on customer experience: A consumer perspective,"ResearchGate,2023.[Online].Available:https://www.researchgate.net/publication/375961142_The_impact_of_automation_and_optimization_on_customer_experience_a_consumer_perspective

Teenie Fung, "The Evolution of Digital Transformation in Customer Service," Hypertype AI, 2025. [Online]. Available: https://www.hypertype.ai/post/digital-transformation-customer-service

Cédric Mestdagh, "Case Management Theory, Modelling,

Limitations and Tools: An Overview, Ghent University, 2015. [Online]. Available: https://libstore.ugent.be/fulltxt/RUG01/002/215/105/RUG01-002215105_2015_0001_AC.pdf

Estela Fernández Sabiote and Sergio Román, "The multichannel customer’s service experience: Building satisfaction and trust," ResearchGate, 2016. [Online]. Available: https://www.researchgate.net/publication/275348498_The_multichannel_customer's_service_experience_building_satisfaction_and_trust

Igboanugo David Ugochukwu, "The Impact of Artificial Intelligence on Customer Service," DZone, 2024. [Online]. Available: https://dzone.com/articles/the-impact-of-artificial-intelligence-on-customer

Mary Kearl, "The Impact of Digital Transformation on Customer Experience," Medallia, 2024. [Online]. Available: https://www.medallia.com/blog/digital-transformation-customer-experience-impact/

Deloitte, "Calculating real ROI on intelligent automation (IA),". [Online]. Available: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/technology-media-telecommunications/blue-prism-white-paper-final.pdf

Flip, "How Will Automation Impact My Customer Service KPIs?" FlipCX, 2021. [Online]. Available:https://flipcx.com/perspectives/how-will-automation-impact-my-customer-service-kpis/

Rohan C and Jayadeep Subhashis, "Customer Service Technology: Examples and Trends to Consider," Sprinklr, 2025. [Online]. Available: https://www.sprinklr.com/blog/customer-service-technology/

Microsoft, "Power Platform Well-Architected," Microsoft Documentation. [Online]. Available: https://learn.microsoft.com/en-us/power-platform/well-architected/

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Published

2025-07-14

How to Cite

Kesavareddi, N. K. R. (2025). Revolutionizing Customer Service: Adaptive Workflow Automation for Case Management. International Journal of Computing and Engineering, 7(8), 51–62. https://doi.org/10.47941/ijce.2941

Issue

Section

Articles