Unified AI Framework for Intelligent Decision Support Secure Data Governance and Scalable Enterprise Architecture
DOI:
https://doi.org/10.15662/IJEETR.2026.0801024Keywords:
Unified AI Framework, Intelligent Decision Support, Data Governance, Enterprise Applications, Machine Learning, Cloud Computing, Microservices, Data Security, Scalable Architecture, Real-Time AnalyticsAbstract
Modern enterprises are increasingly dependent on artificial intelligence to support decision-making, ensure data-driven governance, and scale digital applications across distributed environments. However, most existing systems operate in fragmented silos where decision intelligence, data governance, and application scalability are treated as independent concerns. This paper proposes a Unified AI Framework for Intelligent Decision Support, Secure Data Governance, and Scalable Enterprise Applications that integrates these three critical dimensions into a cohesive architecture. The framework combines machine learning–driven decision engines, policy-based data governance mechanisms, and cloud-native scalable microservices to ensure seamless interoperability across enterprise systems. It leverages advanced analytics, real-time data pipelines, and AI governance models to improve transparency, accountability, and performance efficiency. The proposed architecture also incorporates security-by-design principles, including encryption, access control, and auditability, to ensure compliance with regulatory standards. Furthermore, the framework supports adaptive scaling through containerization and orchestration technologies, enabling enterprises to handle dynamic workloads efficiently. By unifying these capabilities, the framework enhances operational intelligence, reduces system complexity, and improves decision accuracy. The study highlights how integrated AI ecosystems can transform enterprise digital infrastructure into intelligent, secure, and self-sustaining environments capable of supporting next-generation business applications
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