Recent advances in Artificial Intelligence (AI) applied to Human–Computer Interaction (HCI) have been characterized by the convergence of immersive technologies, semantic reasoning, and data-centric learning paradigms. In augmented reality (AR), AI enables real-time interaction by integrating computer vision and contextual understanding into dynamic environments, although it simultaneously introduces new security vulnerabilities that require robust AI-driven protection mechanisms. In parallel, AI-driven cybersecurity has evolved toward proactive and adaptive models that leverage machine learning for real-time threat detection, anomaly analysis, and predictive mitigation, significantly enhancing the resilience of digital systems. Ontologies further strengthen this landscape by providing structured, semantically rich representations of cybersecurity knowledge, facilitating interoperability, automated reasoning, and intelligent threat assessment. Additionally, advances in visual analytics and time series foundation models are enabling the processing of large-scale temporal and multimodal datasets, supporting more sophisticated data interpretation and decision-making processes in complex environments. Modern computer vision systems leverage deep learning architectures such as convolutional neural networks and vision transformers to extract high-level features, enabling accurate object recognition, pattern detection, and scene understanding. Advances in multimodal AI systems—capable of integrating text, images, audio, and video—have become essential for achieving more comprehensive and context-aware intelligence, especially in domains such as medical imaging and interactive systems. Based on these advances highlight, this regular issue presents the most notable research in this direction.