Policy-driven decision intelligence models for adaptive AI-native cloud infrastructure

The digital environment has changed through AI-native cloud infrastructure development which needs sophisticated decision-making frameworks exceeding traditional heuristics with static automation approaches. Artificial intelligence (AI) along with adaptive architectures and policy- based governance systems have produced policy-driven decision intelligence (PDDI) models which operate in the complex and dynamic nature of cloud ecosystems. The models combine machine learning with reinforcement learning and formalized policy constraints to deliver automatic context-aware adaptation to changing workloads and business objectives and regulatory requirements.
This study deeply examines PDDI implementation in AI-native cloud environments which operate with dynamic capabilities. The paper examines the structure of models and their essential modules together with the decision-making processes. The research combines simulation-based modeling with real-time telemetry analysis and constraint-aware optimization on cloud-native orchestration platforms. The integration of intelligent policies directly into cloud system operations through PDDI allows continuous strategic alignment and regulatory compliance as well as system resilience and operational performance.
The analysis identifies crucial technical obstacles surrounding policy conflict resolution together with explainability methods and multi-objective optimization. The study investigates the implementation and practical applications which include autonomous infrastructure management together with service reliability engineering and regulatory compliance automation. The results demonstrate that policy-aware intelligence plays a vital role in future autonomous cloud platforms which presents guidelines for developing self-governing systems to operate in the volatile modern digital environment. The research joins the expanding conversation about developing intelligent cloud management frameworks which are policy-focused for the upcoming computing generation.