Cloud-Native AI Solutions: Transforming enterprise application development

Cloud-native artificial intelligence represents a transformative paradigm shift in enterprise application development, fundamentally altering how organizations design, deploy, and scale AI-powered solutions. The convergence of cloud computing infrastructure with advanced AI capabilities has created a rapidly expanding market with significant growth projections through 2028. Major cloud platforms, including AWS, Microsoft Azure, and Google Cloud, have established themselves as foundational elements in this ecosystem, offering specialized services that significantly optimize development cycles and infrastructure costs. The architectural evolution toward containerization, microservices, and serverless computing has yielded substantial improvements in scalability, resource utilization, and operational efficiency. Data management strategies have similarly evolved, with cloud-based data lakes and distributed computing frameworks enabling organizations to process massive datasets with unprecedented speed and efficiency. The emergence of MLOps has streamlined model lifecycle management, enabling faster deployment, reducing failure rates, and enhancing governance and compliance, thereby making AI development more robust and reliable. As cloud-native AI implementations mature, organizations are increasingly focusing on security, compliance, and ethical considerations, implementing comprehensive frameworks that balance innovation with responsibility and regulatory requirements.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.17265276
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Cloud-Native AI Solutions: Transforming enterprise application development

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Phylogenetic Studies
article

Cloud-Native AI Solutions: Transforming enterprise application development

article en

Abstract

Cloud-native artificial intelligence represents a transformative paradigm shift in enterprise application development, fundamentally altering how organizations design, deploy, and scale AI-powered solutions. The convergence of cloud computing infrastructure with advanced AI capabilities has created a rapidly expanding market with significant growth projections through 2028. Major cloud platforms, including AWS, Microsoft Azure, and Google Cloud, have established themselves as foundational elements in this ecosystem, offering specialized services that significantly optimize development cycles and infrastructure costs. The architectural evolution toward containerization, microservices, and serverless computing has yielded substantial improvements in scalability, resource utilization, and operational efficiency. Data management strategies have similarly evolved, with cloud-based data lakes and distributed computing frameworks enabling organizations to process massive datasets with unprecedented speed and efficiency. The emergence of MLOps has streamlined model lifecycle management, enabling faster deployment, reducing failure rates, and enhancing governance and compliance, thereby making AI development more robust and reliable. As cloud-native AI implementations mature, organizations are increasingly focusing on security, compliance, and ethical considerations, implementing comprehensive frameworks that balance innovation with responsibility and regulatory requirements.

Zenodo (CERN European Organization for Nuclear Research)
University of Greenwich (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 47%
Genomics and Phylogenetic Studies
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