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Digitalization and the Transformation of
the Healthcare Sector

Digitalization and the Transformation of the Healthcare Sector

Risk Tolerance, Financial Stress, and Human-Centered AI

Behavioral Personal Finance

Innovations in Intelligent Internet of Everything IoE

Biomedical Applications of AI and IoMT in Smart Healthcare

Turn AI investment into scalable business impact by enabling your workforce to build the solutions they actually need. From AI Users to Solution Builders is a strategic guide for senior AI, technology, and transformation leaders who want to move beyond underperforming, centralized AI initiatives, and unlock real enterprise value. As organizations struggle to translate AI into measurable results, this book shows how shifting from top-down deployment to workforce-led solution building creates faster adoption, stronger ROI, and sustained innovation. Written by experienced AI leader Wei Manfredi, this book combines strategic insight with practical execution. It draws clear parallels between failed digital transformation efforts and current AI adoption challenges, while demonstrating how natural language interfaces are reshaping access to AI. By enabling non-technical professionals to design their own tools, organizations can embed AI directly into workflows, decision-making, and daily operations. You'll learn how to: - Shift from centralized AI models to workforce-driven innovation - Enable employees to build AI solutions for real workflows - Design scalable infrastructure for AI solution development - Apply change management to overcome resistance and drive adoption &gt;Featuring real-world examples from organizations including Lululemon, Google, Oracle, and JPMorgan Chase, this book provides a proven framework for embedding AI into everyday collaboration, accelerating innovation, and future-proofing your organization's competitive advantage. Themes include: AI strategy, AI adoption, workforce transformation, AI governance, enterprise AI, change management

Scaling AI Across Your Organization

From AI Users to Solution Builders

A Practical Prescription for Medical, Financial, and Personal Fulfillment

The New Physician's Handbook

The Unintended Consequences of the AI, Robotics and Biotech Revolution

A Perfect World

Should we give up privacy to fight disease, for national security, or to help train AI systems? Recent crises, from the Covid-19 pandemic to the Russian invasion of Ukraine, from Gaza and Afghanistan to the seemingly unstoppable rise of AI, have put privacy under severe pressure. Privacy in Crisis argues the opposite: these crises show that privacy needs to be protected even more. Privacy in Crisis looks at vital current issues: at political manipulation and misinformation, government surveillance, racial tension, hybrid and cyberwarfare (and real wars, such as those in Ukraine and Gaza), the overwhelming power of the internet giants, and surveillance society, and how interference with privacy is key in all of them. It shows how specific crises bring many of these issues together in perfect storms of privacy invasion. The different threats to our privacy revealed by these crises tell parallel stories and are inextricably linked. There are common themes and common technologies - the threats involve the same data, the same profiling systems and the same approaches. In many cases the systems are run or owned by the same small set of companies, controlled by the same few people. Addressing them is difficult but possible - this essential book outlines how.

Law and Policy in Times of Extremism, Pandemics, and War

Privacy in Crisis

De Gruyter Studium

Das Lehrbuch bietet eine managementorientierte Einführung in das Fach. In der 6. Auflage wurde es vollständig überarbeitet. Anhand zwei durchgängiger Fallstudien und Aufgaben mit Lösungen bietet es viele Anwendungsmöglichkeiten. Für Lehrende wird ein umfassendes Onlineangebot angeboten. Auf der Website zum Lehrbuch stehen umfangreiche E-Learning-Materialien je Lerneinheit zum Download zur Verfügung, die sich einfach in Moodle integrieren lassen.

Das Lehrbuch bietet eine managementorientierte Einführung in das Fach. In der 6. Auflage wurde es vollständig überarbeitet. Anhand zwei durchgängiger Fallstudien und Aufgaben mit Lösungen bietet es viele Anwendungsmöglichkeiten. Für Lehrende wird ein umfassendes Onlineangebot angeboten. Auf der Website zum Lehrbuch stehen umfangreiche E-Learning-Materialien je Lerneinheit zum Download zur Verfügung, die sich einfach in Moodle integrieren lassen.

Ein fallstudienbasiertes Lehrbuch

Einführung in die Wirtschaftsinformatik

Business Statistics of the United States

Business Statistics of the United States is a comprehensive and practical collection of data from as early as 1913 that reflects the nation's economic performance. It provides several years of annual, quarterly, and monthly data in industrial and demographic detail, including key indicators such as: gross domestic product, personal income, spending, saving, employment, unemployment, the capital stock, and more. Business Statistics of the United States is the best place to find historical perspectives on the U.S. economy. Of equal importance to the data are the introductory highlights, extensive notes, and figures for each chapter that help users to understand the data, use them appropriately, and, if desired, seek additional information from the source agencies. Business Statistics of the United States provides a rich and deep picture of the American economy and contains approximately 3,500 time series. The data are predominantly from federal government sources, including: ·Board of Governors of the Federal Reserve System ·Bureau of Economic Analysis ·Bureau of Labor Statistics ·Census Bureau ·Employment and Training Administration ·Energy Information Administration ·Federal Housing Finance Agency ·Department of the Treasury

Patterns of Economic Change

Business Statistics of the United States 2026

Modern Trends In Financial Engineering

Multiscale Financial Data Analytics and Machine Learning offers a systematic and comprehensive study on the multiscale approach to financial data analytics and machine learning. This book covers an array of multiscale methods to discover the properties of various timescales embedded in a financial time series, including noise-assisted empirical mode decomposition methods. Important interpretable multiscale outputs from the estimation are recognized as a new set of features that can be used for machine learning. The feature selection problem for machine learning is examined in this volume.This book offers an applied quantitative approach that combines novel analytical methodologies and practical applications to a wide array of examples with real-world data. It is self-contained and organized in its presentation. The explanations of the methodologies are both accessible and detailed enough to capture the interest of the curious student or researcher. Step-by-step descriptions of the algorithms are provided for straightforward implementation.

Multiscale Financial Data Analytics And Machine Learning

Platform Supply Chains in the AI Era

This open access book provides a systematic and in-depth analysis of the critical risks inherent in modern platform-based supply chains. Employing rigorous analytical methods, including game theory and advanced, computationally efficient simulation techniques, it delves into three core areas: operational risks, information and data risks, and quality and compliance risks. The book moves beyond traditional supply chain paradigms to address challenges unique to the platform economy. This includes the strategic threat of platforms using seller data to launch competing products, the complex trade-offs in managing third-party product quality, the impact of reactive capacity on quality decisions, and the challenge of optimizing inventory across networks of unprecedented scale.
 
 It is an essential resource for graduate students, academic researchers, and advanced practitioners in the fields of operations management, supply chain management, and information systems. The content is suitable for readers with a graduate-level understanding of these disciplines.

Risk Management

Platform Supply Chains 5

An executive operating system for leading AI-driven strategic transformation Intelligence as a Commodity: Human Judgment as a Competitive Advantage delivers a structured leadership playbook for executives navigating AI adoption. Written by Rajeev Kapur, who built a billion-dollar business at Dell, and Jason Hunter, a senior consultant for the Blue Ocean Strategy Network, the book moves beyond AI trends to provide actionable frameworks for strategic foresight, organizational redesign, and ethical AI governance at the enterprise level. The book introduces flagship tools including HorizonAI for scenario-based strategic planning, HealthCheckAI for operational resilience assessment, and AI Deep Blue Strategy for AI-driven market innovation. Additional frameworks cover Executive Archetypes, the AI Leadership OS, AI Organizational OS, and Collective Intelligence Framework, each designed to shift organizations from reactive AI adoption to proactive, sustainable competitive positioning. Readers will also find: <ul> <li>Frameworks for assessing AI readiness and prioritizing initiatives across enterprise operations and strategy functions</li> <li>Tools for integrating human-AI collaboration while managing ethical, operational, and governance risk at scale</li> <li>Scenario-based strategic planning methods using HorizonAI to anticipate market shifts and technology disruptions</li> <li>Organizational redesign approaches for building agility and hybrid intelligence into existing leadership structures</li> <li>Guidance on embedding ethical AI governance and risk management into enterprise-wide adoption programs</li> </ul> Written for C-suite executives, directors, entrepreneurs, MBA participants, and consultants overseeing strategy, operations, and innovation, this book provides the frameworks and tools needed to lead AI-driven transformation with clear organizational design, ethical governance, and measurable business outcomes at the enterprise level.

Human Judgment as a Competitive Advantage

Intelligence as a Commodity

Digitalization and the Transformation of the Healthcare Sector

Weitere Titel zum Thema