Description
Book SynopsisArtificial Intelligence (AI) is being rapidly introduced into the workplace, creating debate around what AI means for our work and organizations. This book gives grounded counterweight to provocative newspaper headlines by using in-depth case studies of eight organizations’ experiences of implementing and using AI, providing readers with a solid understanding of what is actually happening in practice.
Critical yet constructive, the authors address the challenges of implementing AI: organizing for data, testing and validating, algorithmic brokering, and changing work. Using a combination of existing literature and thorough practical examples, they provide answers to questions such as: What data do I need? When is a system good enough to actually take over tasks? And how can my employees be prepared for working with AI? The book presents four recommendations for WISE management of AI, requiring work-related insights, interdisciplinary knowledge, sociotechnical change processes, and ethical awareness.
Offering insight into the unique characteristics of AI in organizations, this book will be essential reading for scholars of business and management, data analytics and information systems, technology and innovation, and computer science. With practical recommendations for managing the challenges of AI, it will also provide business managers with reflections to improve their own AI development and implementation processes.
Trade Review‘Wonderfully written, this book will resonate with every manager who is currently grappling with implementing AI in their organization. By analyzing real-life case studies, the authors go way beyond the AI hype and dive into the intricate organizational and work challenges that arise with the introduction of AI in the workplace, providing actionable insights. A must read for all decision makers, developers and technology brokers at incumbent organizations!’ -- Stella Pachidi, University of Cambridge, UK
Table of ContentsContents: 1. Introduction to managing AI wisely 2. What is AI? 3. Perspectives on AI and work 4. Methods and introduction to cases 5. Organizing for data 6. Testing and validating 7. Algorithmic brokers 8. Changing work 9. How can AI systems be managed wisely? Index
