This issue of the Journal of Artificial Intelligence in Information Technology presents a curated collection of studies that reflect the growing integration of artificial intelligence within complex IT infrastructures, emphasizing both theoretical advancement and practical implementation. The contributions in this issue explore diverse applications of AI, including deep learning–driven predictive analytics for system failure detection, AIoT-enabled decision support systems for infrastructure monitoring, and context-aware neural approaches for code refactoring in legacy systems. Several articles further investigate performance optimization and analytical evaluation, such as comparative assessments of text-to-video models and anomaly detection in system log data using convolutional neural networks. In addition, this issue highlights applied frameworks for real-time network intrusion detection and includes a systematic review on AI-driven expert decision support systems for resource optimization in enterprise environments. Collectively, these works demonstrate a strong emphasis on scalable, real-time, and intelligent IT solutions that bridge the gap between research and deployment. The contributions are enriched by international authorship from Indonesia, the Republic of Korea, and India, reinforcing the journal’s commitment to global collaboration and multidisciplinary innovation in AI-driven information technology.
This issue is published as an early release (early publish), providing timely access to the latest research findings prior to formal issue compilation.
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