Piridi, Sarat (2025) Cross-Industry Applications of Copilot Automation. World Journal of Advanced Research and Reviews, 26 (2). pp. 4413-4420. ISSN 2581-9615
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Abstract
Copilot automation technology has revolutionized operational efficiency across diverse industry sectors through the integration of AI-driven solutions. The combination of Copilot agents with computer-use flows creates powerful automation capabilities applicable in multiple business environments. At the foundation of these implementations lies a robust architectural framework consisting of three core components: AI Builder for data extraction, Copilot Agents for decision-making logic, and Computer-Use Flows for legacy system integration. Financial services organizations have leveraged these technologies to streamline loan processing while maintaining regulatory compliance. Retail implementations have enhanced inventory management across distributed locations through centralized reconciliation systems. Manufacturing environments benefit from accelerated procurement processes and improved supplier integration. Utility companies have extended the lifespan of legacy infrastructure through non-disruptive integration approaches. Performance metrics consistently demonstrate improvements in processing speed, error reduction, and maintenance cost elimination. The technical value proposition encompasses computational resource optimization, developer productivity enhancement, and infrastructure consolidation. By implementing established design patterns and embracing emerging capabilities like enhanced natural language understanding, organizations can achieve substantial operational improvements without requiring wholesale system replacement.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjarr.2025.26.2.2029 |
Uncontrolled Keywords: | Copilot automation; Cross-industry implementation; Intelligent process automation; Legacy system integration; Multi-tenant architecture |
Depositing User: | Editor WJARR |
Date Deposited: | 20 Aug 2025 11:52 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/3740 |