AI Powered Enterprise Engineering for Cloud Native Digital Transformation and Cyber Resilience Frameworks
Abstract
Artificial Intelligence (AI) has emerged as a transformative technology that enables organizations to modernize enterprise engineering practices while strengthening cloud-native digital transformation and cyber resilience. The increasing complexity of enterprise systems, rapid cloud adoption, and growing cybersecurity threats require organizations to adopt intelligent frameworks capable of supporting automation, scalability, adaptability, and continuous protection. AI-powered enterprise engineering integrates machine learning, predictive analytics, intelligent automation, cloud-native architectures, and cybersecurity mechanisms to improve business performance and operational resilience. Cloud-native technologies such as microservices, containers, Kubernetes orchestration, and serverless computing provide flexible and scalable infrastructures, while AI enhances decision-making through real-time analytics and autonomous operations. Simultaneously, cyber resilience frameworks utilize AI-driven threat detection, anomaly identification, automated incident response, and predictive risk assessment to protect enterprise assets from sophisticated cyberattacks. This study proposes an integrated enterprise engineering framework that combines AI, cloud-native computing, and cybersecurity into a unified architecture for digital transformation. The research methodology adopts a design science approach supported by enterprise architecture modeling, simulation, comparative analysis, and cybersecurity evaluation. The proposed framework demonstrates improvements in scalability, operational efficiency, regulatory compliance, business continuity, and cyber resilience while reducing operational costs and security risks. The study contributes to the development of intelligent enterprise systems capable of supporting sustainable digital transformation in dynamic and increasingly complex business environments
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 10 |
| Number | 2 |
| Pages | 18787-18795 |
| Published | 2026-04-15 |
| Issue | Vol. 10 No. 2 (2026): International Research Journal of Innovative Engineering (IRJIE) |
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