AI and Machine Learning Advances

The artificial intelligence, microservices architecture, and cloud computing convergence is a significant shift in modern enterprise system design and functioning. Cloud-native environments allow applications to be broken down into modular services independently deployable, expandable, and manageable to enhance the flexibility of the system and its resilience to operations. Meanwhile, the incorporation of artificial intelligence into distributed architectures suggests the introduction of intelligent decision-making functions, which can be used to optimise the use of resources, automate their work, and increase the responsiveness of the systems. This paper discusses the architectural integration of artificial intelligence and microservices in Microsoft .NET and Azure cloud environments on the aspects of scalability, security governance, and intelligent data orchestration of modern enterprise architectures. An analytic framework based on reviews was used to generalise the literature on the topic published between 2018 and 2025. Scholarly literature was searched in the large scientific databases and studies on the subject were identified and analysed based on three main dimensions; the mechanisms of scalability, the security framework and the strategy of intelligent data orchestration. This analysis shows that distributed microservices systems scale dynamically and can ensure service reliability in heterogeneous cloud environments due to the use of containerisation and orchestration technologies. Artificial intelligence also augments these architectures by providing predictive resource allocation, automated workload management and adaptive system optimisation. Nevertheless, the complexity of the security management is also expanded due to the decentralised nature of microservices environments, as well as due to the presence of new risks related to service communication and vulnerabilities of machine learning models. In general, the results reveal that a combination of artificial intelligence and cloud-native microservices frameworks allows creating expandable, resilient, and intelligent enterprise environments with the potential of supporting data-intensive digital services. The paper has also brought out the relevance of a strong governance system, safe orchestration systems, and dynamic data management techniques to achieve the consistent functionality of disseminated clever cloud infrastructures.