Advances in Data Analytics, AI, and Smart Systems – serie
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3 produkter
3 produkter
768 kr
Skickas inom 10-15 vardagar
714 kr
Skickas inom 10-15 vardagar
This book explores the architecture and framework for co-creating the most valuable and promising data in the future Internet, often referred to as Web 3.0, from the end user’s perspective. Unlike the current platform economy, where user’s daily usage and activity data is predominantly held by individual organizations, Web 3.0 advocates for decentralized data management across interconnected platforms. This approach aims to fully utilize the vast amounts of data generated by the increasingly connected physical world. The book explains how Web 3.0 can be developed with fundamental and technological support to enhance decentralized data management and maximize benefits for end users. Additionally, it presents two use cases to illustrate how value co-creation can be achieved using Web 3.0.The book is aimed primarily at students from business and engineering schools. It also serves as a valuable teaching resource for instructors in management information systems (MIS), information systems, information science and technology, and data and computing sciences. Additionally, professionals interested in digital transformation, blockchain technology, data analytics, AI, and digital economy policymaking will find it highly relevant.
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Artificial intelligence is no longer a standalone technology. It is reshaping how organizations operate, compete, and create value. Yet most firms remain stuck at early stages of adoption, focusing on isolated use cases rather than true transformation.This book provides a structured, actionable framework to help leaders move beyond experimentation toward enterprise-wide impact. Built around a four-level model consisting of Automation, Personalization, Operational Innovation, and Business Model Innovation, the book offers a clear roadmap for how AI can drive measurable value across different stages of organizational maturity.Drawing on real-world cases across industries, each chapter demonstrates how leading organizations are applying AI in practice, from improving efficiency and customer experience to redesigning core operations and creating entirely new business models. These examples are grounded in concrete outcomes, enabling readers to understand not only what works, but why.A defining feature of the book is its integrated approach to risk and governance. Each case is accompanied by a structured analysis combining PwC’s auditing risk framework (financial, operational, and reputational risks) with legal and regulatory perspectives. This dual lens equips decision-makers to scale AI responsibly while navigating increasing scrutiny around compliance, accountability, and trust.Designed for business leaders, AI strategists, and legal professionals, this book bridges the gap between technical possibility and organizational reality. It provides practical tools, strategic insights, and a disciplined framework to help organizations capture the value of AI, while managing its risks.