Designing Secure Agentic AI Frameworks for Enterprise Cloud Data Analytics and Intelligent Digital Transformation
DOI:
https://doi.org/10.15680/IJMRSETM.2025.0104005Keywords:
Agentic AI, Enterprise Cloud Analytics, Artificial Intelligence, Cloud Computing, Intelligent Digital Transformation, Zero Trust Security, Enterprise Data Analytics, Machine Learning, Deep Learning, Cloud Security, Intelligent Automation, Predictive Analytics, Explainable AI, Data Governance, Hybrid CloudAbstract
The rapid advancement of cloud computing and Artificial Intelligence (AI) has accelerated enterprise digital transformation, enabling organizations to process massive volumes of data while improving operational efficiency and business intelligence. However, the increasing adoption of cloud-native platforms, distributed applications, and autonomous AI systems has introduced significant security, privacy, governance, and compliance challenges. This research proposes a secure Agentic AI framework for enterprise cloud data analytics that integrates autonomous intelligent agents, cloud-native computing, Zero Trust Security, machine learning, and intelligent automation to support secure digital transformation. The proposed framework enables AI agents to autonomously collect, analyze, govern, and optimize enterprise data while continuously monitoring cloud infrastructure, detecting cyber threats, enforcing security policies, and orchestrating automated incident response. Predictive analytics, behavioral intelligence, and deep learning algorithms enhance real-time decision-making, anomaly detection, and operational optimization across hybrid and multi-cloud environments. The framework further incorporates identity and access management, encryption, data governance, explainable AI, compliance automation, and security orchestration to ensure regulatory adherence and trustworthy AI operations. By combining secure cloud computing with Agentic AI, enterprises can improve business intelligence, strengthen cybersecurity, optimize resource utilization, accelerate decision-making, and increase organizational resilience. The proposed architecture provides a scalable, adaptive, and intelligent platform capable of supporting secure enterprise analytics and sustainable digital transformation in rapidly evolving technological environments.
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