AI-Enabled Enterprise Integration Using APIs and Event-Driven Architecture for Cloud Data Interoperability and Workflow Automation

Authors

  • Venkata Raghavendra Miriampally Professor, Electrical and Computer Engineering Department, Adama Science & Technology University, Ethiopia Author

DOI:

https://doi.org/10.21590/

Keywords:

Artificial Intelligence, Enterprise Integration, APIs, Event-Driven Architecture, Cloud Computing, Data Interoperability, Workflow Automation, Cloud Integration, Intelligent Automation, Microservices

Abstract

Enterprise organizations increasingly operate across heterogeneous cloud platforms, legacy applications, databases, software-as-a-service systems, and distributed digital services, creating significant challenges for data interoperability and workflow automation. Traditional point-to-point integration approaches often produce tightly coupled architectures, duplicated data, high maintenance requirements, and limited scalability. This paper examines an AI-enabled enterprise integration model that combines Application Programming Interfaces (APIs), event-driven architecture, cloud computing, and artificial intelligence to support interoperable data exchange and intelligent workflow automation. The proposed approach uses APIs as standardized integration interfaces and event-driven mechanisms to enable asynchronous communication between distributed enterprise systems. Artificial intelligence contributes through intelligent event classification, workflow prediction, anomaly detection, semantic data mapping, and automated decision support. The study adopts a conceptual research methodology based on systematic analysis of existing literature and architectural synthesis. Particular attention is given to how AI can reduce integration complexity while improving responsiveness, adaptability, data quality, and operational efficiency. The research also considers challenges involving security, governance, interoperability standards, data privacy, model reliability, and organizational readiness. The findings indicate that combining APIs and event-driven architecture with AI can provide a flexible foundation for cloud data interoperability and workflow automation. However, successful implementation requires strong governance, standardized interfaces, observability, security controls, and human oversight. The study provides an architectural perspective for organizations seeking scalable and intelligent enterprise integration capabilities.

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Published

2022-09-30

How to Cite

Miriampally, V. R. (2022). AI-Enabled Enterprise Integration Using APIs and Event-Driven Architecture for Cloud Data Interoperability and Workflow Automation. International Journal of Technology, Management and Humanities, 8(04), 50-56. https://doi.org/10.21590/

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