An Explainable AI Framework for Intelligent API Governance and Compliance in Cloud-Based Enterprise Systems

Bruno Souza; Bruno Souza

doi:10.15662/ijetemr.2023.0806003

An Explainable AI Framework for Intelligent API Governance and Compliance in Cloud-Based Enterprise Systems

Bruno Souza

Java Software Architect, SouJava, Brazil

Abstract

The rapid adoption of cloud computing, microservices, and Application Programming Interfaces (APIs) has transformed enterprise information systems by enabling seamless integration, scalability, and digital service delivery. However, the increasing complexity of cloud-based API ecosystems presents significant challenges in governance, regulatory compliance, security, and operational transparency. Traditional API governance approaches primarily rely on static policies, manual auditing, and rule-based monitoring, which often fail to adapt to evolving enterprise environments and complex compliance requirements. This research proposes an Explainable Artificial Intelligence (XAI) framework for intelligent API governance and compliance in cloud-based enterprise systems. The proposed framework integrates explainable machine learning, automated policy enforcement, continuous compliance monitoring, anomaly detection, and transparent decision support to improve governance effectiveness while ensuring accountability and trust. Explainable AI enables administrators to understand the reasoning behind governance decisions, security alerts, compliance assessments, and API policy recommendations through interpretable models and human-readable explanations. The framework supports real-time monitoring of API interactions, dynamic policy validation, risk assessment, and regulatory compliance across distributed cloud infrastructures. A conceptual research methodology supported by an extensive literature review is employed to design and evaluate the framework. The proposed architecture demonstrates the potential to enhance transparency, regulatory adherence, operational efficiency, security, and decision-making while reducing governance complexity. The study contributes to the development of trustworthy AI-enabled enterprise systems capable of supporting intelligent API governance in increasingly dynamic cloud computing environments

Article Information

Journal	International Journal of Emerging Trends in Engineering and Management Research
Volume (Issue)	Vol. 8 No. 6 (2023): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR)
DOI	https://doi.org/10.15662/ijetemr.2023.0806003
Pages	14697-14708
Published	December 12, 2023
Copyright	All rights reserved
Open Access	This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite	Bruno Souza (%2023). An Explainable AI Framework for Intelligent API Governance and Compliance in Cloud-Based Enterprise Systems. International Journal of Emerging Trends in Engineering and Management Research , Vol. 8 No. 6 (2023): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) , pp. 14697-14708. https://doi.org/10.15662/ijetemr.2023.0806003

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