Next Generation Enterprise Computing Through Hybrid AI FinOps Blockchain and Healthcare Analytics
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Abstract
The rapid evolution of enterprise computing has transformed organizational strategies by integrating intelligent technologies that enhance operational efficiency, financial governance, data security, and healthcare service delivery. Next-generation enterprise computing combines Artificial Intelligence (AI), Financial Operations (FinOps), blockchain technology, and healthcare analytics into a unified framework capable of supporting sustainable digital innovation. AI enables intelligent automation, predictive analytics, and data-driven decision-making across enterprise environments, while FinOps provides financial accountability and optimized cloud resource utilization to reduce operational costs. Blockchain technology strengthens trust through decentralized, transparent, and immutable transaction management, ensuring secure data exchange among multiple stakeholders. Healthcare analytics leverages large-scale clinical and operational datasets to improve patient outcomes, optimize resource allocation, and support evidence-based healthcare management. The integration of these technologies creates an adaptive digital ecosystem that improves organizational resilience, regulatory compliance, cybersecurity, and business agility. This paper proposes a hybrid enterprise computing framework that combines AI-driven intelligence, FinOps governance, blockchain-enabled trust, and healthcare analytics to address the growing demands of digital transformation. The framework emphasizes scalable cloud infrastructure, secure information sharing, predictive decision support, and sustainable innovation while minimizing operational risks and financial inefficiencies. The proposed approach demonstrates how interdisciplinary technological convergence can enable intelligent enterprises to achieve long-term competitiveness, environmental sustainability, improved healthcare services, and resilient digital ecosystems capable of addressing future technological and organizational challenges
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