Cloud Native Enterprise Intelligence through Autonomous AI and Predictive Analytics for Strategic Decision Making
DOI:
https://doi.org/10.15662/IJEETR.2026.0803011Keywords:
Cloud-native enterprise intelligence, autonomous artificial intelligence, predictive analytics, strategic decision making, machine learning, cloud computing, business intelligence, digital transformation, intelligent automation, enterprise analytics, data-driven decision making, cloud architecture, organizational intelligence, real-time analytics, innovation managementAbstract
The rapid digital transformation of modern enterprises has generated unprecedented volumes of data from cloud platforms, connected devices, business applications, and customer interactions. Organizations increasingly require intelligent systems capable of transforming this data into actionable insights that support strategic decision-making. Cloud-native enterprise intelligence, empowered by autonomous artificial intelligence (AI) and predictive analytics, has emerged as a transformative paradigm that enables enterprises to achieve agility, scalability, operational efficiency, and data-driven competitiveness. Autonomous AI systems leverage machine learning, deep learning, reinforcement learning, and intelligent automation to continuously monitor business environments, identify patterns, and make recommendations with minimal human intervention. Predictive analytics further enhances organizational capabilities by forecasting future trends, customer behaviors, operational risks, and market opportunities. Cloud-native architectures provide the computational elasticity, distributed processing, and real-time analytics necessary for implementing advanced AI-driven intelligence systems across enterprise ecosystems. This study explores the integration of cloud-native technologies, autonomous AI, and predictive analytics in enterprise intelligence frameworks for strategic decision-making. The discussion examines theoretical foundations, technological advancements, implementation approaches, and organizational implications. Through an extensive review of existing literature and a comprehensive methodological framework, the study highlights how intelligent cloud-native systems improve decision quality, accelerate innovation, optimize resource allocation, and strengthen competitive advantage. The findings suggest that enterprises adopting autonomous AI-powered predictive intelligence can achieve superior strategic outcomes while addressing challenges related to data governance, security, ethics, and organizational change management
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