Artificial Intelligence (AI) systems are computational frameworks designed to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. These systems integrate algorithms, data, and computing power to enable machines to adapt and improve their performance over time. AI systems encompass a wide range of technologies, including machine learning, natural language processing, computer vision, and autonomous robotics, and they are increasingly applied in domains such as healthcare, finance, cybersecurity, transportation, and smart cities. As they continue to evolve, AI systems are not only transforming industries and enhancing human capabilities but also raising important considerations around ethics, transparency, and trustworthiness.

The International Conference on Artificial Intelligence Systems (AIS 2026) aims to bring together leading researchers, academics, and practitioners from around the world to share their latest findings, innovations, and applications in Artificial Intelligence and intelligent systems. AIS 2026 provides a premier interdisciplinary platform for presenting advances and exchanging insights on the theoretical foundations, cutting-edge technologies, and real-world implementations of AI. AIS 2026 will feature keynote talks, technical paper sessions, workshops, and tutorials covering a wide range of AI topics. We invite submissions of high-quality research papers describing original and unpublished results in all areas of Artificial Intelligence Systems. addresses the use of advanced intelligent systems in providing cybersecurity solutions in many fields, and the challenges, approaches, and future directions. We invite the submission of original papers on all topics related to Intelligent Systems with special interest in but not limited to:

    Machine Learning and Data-Driven Systems
        Deep Learning, Representation Learning, and Transfer Learning
        Reinforcement Learning and Adaptive Systems
        Federated, Distributed, and Edge AI
        Reinforcement Learning and Autonomous Agents
        Federated Learning and Distributed AI Systems
        AI Applications and Intelligent Systems
        Scalable and High-Performance AI Architectures
        Edge AI, Cloud AI, and Embedded Intelligence
        Optimization and Resource-Aware AI Systems

    Natural Language and Multimodal AI
        Natural Language Processing and Understanding
        Speech Recognition and Conversational Agents
        Multimodal Learning and Vision-Language Systems
        Knowledge Representation and Reasoning
        Data Mining, Knowledge Discovery, and Information Retrieval
        Automated Planning and Scheduling

    Generative AI, Foundation Models, and Large Language Models
        Generative AI and Large Language Models (LLMs)
        Explainable and Responsible AI
        Federated, Distributed, and Edge AI
        Reinforcement Learning and Autonomous Agents
        AI for Decision Support Systems
        Natural Language Processing and Computational Linguistics
        Multilingual and Low-Resource Language Models
        Human-Computer Interaction (HCI) and Assistive Technologies
        Conversational AI and Dialogue Systems
        Computational Language and Human-Centered Systems
        Prompt Engineering and Fine-tuning
        Multimodal LLMs
        Agentic AI

    Computer Vision, Image and Video Processing
        Image and Video Understanding
        Object Detection, Recognition, and Tracking
        Multimodal Learning and Vision-Language Systems
        3D Vision and Scene Understanding
        Affective Computing and Emotion Recognition

    Artificial Intelligence Applications
        Robotics and Autonomous Systems
        AI for Healthcare, Smart Cities, and Transportation
        AI in Finance, Education, and Industry 4.0
        AI for Cybersecurity, Privacy, and Digital Trust
        AI Infrastructure and Engineering
        Recommender Systems and Personalization
        AI for Social Good and Humanitarian Applications
        Emerging Trends and Future Directions in AI Systems

    Artificial Intelligence Security
        Responsible and Trustworthy AI
        Explainable AI and Transparency
        Ethical and Societal Implications of AI
        AI Safety, Robustness, and Security
        AI Policy, Regulation, and Governance