Agentic and Generative Artificial Intelligence for Intelligent Automation

Expected date of publication: December 2026

Pages: 250

Edited by: Kwok Tai Chui (Hong Kong Metropolitan University, Hong Kong) and Akshat Gaurav (Ronin Institute, USA, and Asia University, Taichung, Taiwan)

ISBN: To be assigned

Agentic and Generative Artificial Intelligence for Intelligent Automation offers a comprehensive exploration of advances in Agentic AI and Generative Artificial Intelligence (GenAI), focusing on developing intelligent, adaptive, and autonomous systems that can transform traditional automation processes. The book examines how generative models, autonomous agents, and intelligent decision-making frameworks can be integrated to enhance efficiency, flexibility, and adaptability across complex digital and industrial environments.

Unlike conventional automation systems that rely on predefined rules and workflows, Agentic and Generative AI enable intelligent systems to generate content, reason, plan, make decisions, execute tasks, and dynamically respond to changing environments. This book explores the convergence of large language models (LLMs), foundation models, multi-agent systems, reinforcement learning, and intelligent workflow orchestration to support autonomous operations, collaborative problem-solving, and human–AI interaction.

The book brings together fundamental concepts, advanced architectures, enabling technologies, and practical applications of Agentic and Generative AI in intelligent automation. It examines generative modeling techniques, agent-based architectures, autonomous task planning, adaptive decision-making, multi-agent collaboration, and trustworthy AI frameworks. Particular attention is given to applications in smart manufacturing, cybersecurity, healthcare, robotics, intelligent IoT, business process automation, and next-generation digital systems.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Generative AI and autonomous agent architectures.
LLMs and foundation models for automation.
AI-driven content and knowledge generation.
Agentic reasoning, planning, and decision-making.
Multi-agent collaboration and distributed intelligence.
Agentic workflows and process automation.
Reinforcement learning and adaptive intelligence.
Human–AI collaboration and trustworthy automation.
Generative and agentic AI for smart manufacturing.
Automation in cybersecurity, healthcare, robotics, and IoT.
Emerging challenges and future research directions.

Keywords: Agentic Artificial Intelligence, Generative Artificial Intelligence, Intelligent Automation, Autonomous Intelligent Agents, Large Language Models

Table of Contents:

Coming soon.

Readership: Researchers, academics, postgraduate students, and industry professionals in agentic AI, generative artificial intelligence, intelligent automation, and intelligent decision-making.

Kwok Tai Chui

Hong Kong Metropolitan University, Hong Kong

Kwok Tai Chui (Member IEEE) is an associate professor in the Department of Electronic Engineering and Computer Science at Hong Kong Metropolitan University. He received a first-class B.Eng. in electronic and communication engineering, with a minor in business intelligence, and a Ph.D. in electronic engineering from City University of Hong Kong. He worked as a senior data scientist at an Internet of Things company before joining Hong Kong Metropolitan University as a research assistant professor in 2019, later becoming an assistant professor and then an associate professor. His research covers computational intelligence, data science, machine learning, energy monitoring and management, intelligent transportation, smart metering, and healthcare.

He has published more than 300 works, including journal papers, conference papers, book chapters, and edited books. He is a managing editor of the International Journal on Semantic Web and Information Systems, a topic editor of Sensors, and an associate editor of the International Journal of Asian Business and Information Management and the International Journal of Energy Optimization and Engineering. He has also served as a guest editor for Future Generation Computer Systems, the Journal of Innovation and Knowledge, Sustainability, Sensors, Energies, Applied Sciences, and the Journal of Internet Technology. He won first prize in the IEEE Hong Kong Section postgraduate student paper contest in 2013, second prize in the 2014 IEEE Region 10 Student Paper Contest, and best-paper awards at the IEEE International Conference on Consumer Electronics–China in 2014 and 2015. In February 2025, Hong Kong Metropolitan University awarded him its Silver Prize for an enhanced transfer-learning algorithm aimed at small datasets.

Akshat Gaurav

Ronin Institute, USA, and Asia University, Taichung, Taiwan

Akshat Gaurav is a Senior IEEE Member and a recognized researcher listed in the Stanford–Elsevier Top 2% Scientists (Single-Year 2025, 2024) in Artificial Intelligence and Image Processing. He is currently a Senior Researcher at the International Center for AI and Cyber Security Research and Innovations, Asia University, Taiwan. His research spans cybersecurity, AI-driven attack detection, phishing prevention, semantic web technologies, and intelligent IoT systems. He has authored an extensive body of research published in leading venues including IEEE Transactions, Elsevier, Springer, IGI Global, and ACM.

His work has earned multiple accolades, including Best Paper Awards at IEEE/ACM Cluster, Cloud and Internet Computing, and International AI & IoT conferences, as well as Best Oral Presentation at GCCE 2025. Mr. Gaurav also plays active leadership roles in the research community. He served as Session Chair at IEEE GLOBECOM 2025 and previously as Session Co-Chair at IEEE GCCE 2022. In addition, he contributes as a Technical Program Committee (TPC) member and reviewer for premier venues, including IEEE INFOCOM, GLOBECOM, ICC, ICCE, ANTS, and several high-impact IEEE Transactions and ACM journals.

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