Intelligent Enterprise Ecosystems through AI-Driven Security, Privacy and Cloud Innovation Frameworks
DOI:
https://doi.org/10.21590/Keywords:
AI-driven security, enterprise ecosystems, cloud computing, privacy preservation, machine learning, cybersecurity frameworks, digital transformation, data protection, intelligent systems, cloud innovationAbstract
The rapid evolution of digital technologies has transformed enterprises into complex, interconnected ecosystems that rely heavily on cloud infrastructure, artificial intelligence (AI), and data-driven decision-making. However, this transformation introduces significant challenges related to security, privacy, and system resilience. This study explores the development of intelligent enterprise ecosystems through integrated AI-driven security, privacy-preserving mechanisms, and cloud innovation frameworks. It proposes a unified model that leverages machine learning algorithms for threat detection, adaptive security policies, and predictive analytics, while embedding privacy-enhancing technologies such as differential privacy and secure multi-party computation. Additionally, the framework emphasizes cloud-native architectures, including microservices and edge computing, to ensure scalability, flexibility, and real-time responsiveness. The research highlights how the convergence of AI, cybersecurity, and cloud computing enables organizations to build resilient, self-healing, and context-aware systems capable of mitigating risks and ensuring compliance with evolving regulatory standards. Through conceptual analysis and methodological design, this study demonstrates the potential of integrating these technologies to enhance operational efficiency, data integrity, and user trust. The findings contribute to the advancement of enterprise digital transformation strategies by providing a holistic approach to secure and intelligent ecosystem development.
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