附註:Includes bibliographical references and index.
Section 1. Foundations of artificial intelligence and data analytics: a data-driven approach. Chapter 1. Foundations of artificial intelligence and the ever-evolving technological landscape in business ; Chapter 2. AI-driven data analytics in information sciences and organizational management -- Section 2. Artificial intelligence in knowledge engineering and management: (re)shaping the knowledge landscape and fostering innovation. Chapter 3. Artificial intelligence, knowledge engineering, and management ; Chapter 4. Knowledge management tools for reducing the learning curve: a case study ; Chapter 5. Driving innovation ecosystem transformation via digital platforms and knowledge co-creation -- Section 3. Intersection of business intelligence and artificial intelligence on multiple domains. Chapter 6. Creating business process intelligence through value network analysis: a tagging-based approach ; Chapter 7. Creating an information governance program at a college to ultimately implement artificial intelligence, predictive analytics, and prescriptive analytics ; Chapter 8. AI and data analytics for market research and competitive intelligence ; Chapter 9. Artificial intelligence in chess-playing automata: a paradigm for the quiescence phase of a-[Beta] search ; Chapter 10. Smart tourism narratives: maturity matrix and digital transformation -- Section 4. Artificial intelligence prompting digital transformation:ethics, robotics, machine learning, and new trends. Chapter 11. Understanding the ethical and social consequences of data analytics for organizational management in the age of AI: accounting ethics perspective ; Chapter 12. Intelligent industry 4.0: artificial intelligence and robotic process automation as tendsetters.
摘要:"Within information sciences and organizational management, a pressing challenge emerges; How can we harness the transformative power of artificial intelligence (AI) and data analytics? As industries grapple with a deluge of data and the imperative to make informed decisions swiftly, the gap between data collection and actionable insights widens. Professionals in various sectors are in a race to unlock AI's full potential to drive operational efficiency, enhance decision-making, and gain a competitive edge. However, navigating this intricate terrain, laden with ethical considerations and interdisciplinary complexity, has proven to be a formidable undertaking.AI and Data Analytics Applications in Organizational Management, combines rigorous scholarship with practicality. It traverses the spectrum from theoretical foundations to real-world applications, making it indispensable for those seeking to implement AI-driven data analytics in theirorganizations. Moreover, it delves into the ethical and societal dimensions of this revolution, ensuring that the journey toward innovation is paved with responsible considerations. For researchers, scholars, and practitioners yearning to unleash the potential of AI in organizational management, this book is the key to not only understanding the landscape but also charting a course toward transformative change."--
