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Challenges and Opportunities in Artificial Intelligence: Engineering and Management Applications presents a comprehensive exploration of how AI is transforming modern engineering systems and managerial decision-making. The book discusses emerging trends, practical applications, and the evolving role of intelligent technologies in solving real-world problems.
This book examines key domains where Artificial Intelligence is reshaping processes, performance, and innovation. It covers foundational AI concepts, machine learning techniques, intelligent automation, data-driven decision models, and advanced computational methods relevant to engineering disciplines. The chapters highlight AI-enabled solutions in areas such as predictive maintenance, smart manufacturing, robotics, optimization, and sustainable engineering. In management applications, the book addresses AI-supported analytics, decision support systems, workflow automation, and strategic planning powered by big data. It also discusses challenges including ethical concerns, algorithmic transparency, workforce readiness, and cybersecurity risks. Through research-based insights and practical case studies, the book illustrates how AI can enhance efficiency, accuracy, and innovation while also emphasizing the need for responsible and well-governed AI adoption.
This book is intended for researchers, academicians, industry professionals, engineers, and management practitioners seeking to understand the practical integration of AI in real systems. It is also valuable for postgraduate students and policymakers interested in emerging AI technologies, their opportunities, and the strategic challenges associated with their deployment.
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Challenges and Opportunities in Artificial Intelligence: Engineering and Management Applications presents a comprehensive exploration of how AI is transforming modern engineering systems and managerial decision-making. The book discusses emerging trends, practical applications, and the evolving role of intelligent technologies in solving real-world problems.
This book examines key domains where Artificial Intelligence is reshaping processes, performance, and innovation. It covers foundational AI concepts, machine learning techniques, intelligent automation, data-driven decision models, and advanced computational methods relevant to engineering disciplines. The chapters highlight AI-enabled solutions in areas such as predictive maintenance, smart manufacturing, robotics, optimization, and sustainable engineering. In management applications, the book addresses AI-supported analytics, decision support systems, workflow automation, and strategic planning powered by big data. It also discusses challenges including ethical concerns, algorithmic transparency, workforce readiness, and cybersecurity risks. Through research-based insights and practical case studies, the book illustrates how AI can enhance efficiency, accuracy, and innovation while also emphasizing the need for responsible and well-governed AI adoption.
This book is intended for researchers, academicians, industry professionals, engineers, and management practitioners seeking to understand the practical integration of AI in real systems. It is also valuable for postgraduate students and policymakers interested in emerging AI technologies, their opportunities, and the strategic challenges associated with their deployment.