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Strategic Insights and Case Studies on
Navigating an Entrepreneurial Landscape

Strategic Insights and Case Studies on Navigating an Entrepreneurial Landscape

Algorithmic Management: Artificial Intelligence and the Transformation of Organizations is the first comprehensive textbook designed to prepare management students to engage critically and responsibly with artificial intelligence in organizations. Bringing together classical management theory, contemporary AI applications, and systematic power analysis, the book equips future managers to both harness AI's potential and confront its risks.Structured in three parts, the book begins with foundational frameworks-socio-technical systems theory, technology and society perspectives, and core management theories reinterpreted for the AI era. It then examines applications across all major management functions-Marketing, HR, Finance, Operations, Supply Chain, and Strategy-using over 30 real-world case studies drawn from different industries, parts of the world, and types of organizations from multinational corporations to nonprofits and social ventures. The final section addresses organizational design, leadership, governance, and the future of algorithmic organizations. Throughout, pedagogical features-learning objectives, vignettes, discussion questions, toolkits, and ethical dilemmas-make the book classroom-ready and adaptable across MBA, undergraduate, and executive education settings. The text advances an approach of pragmatic criticality: AI is neither celebrated uncritically nor rejected outright but treated as a socio-technical phenomenon requiring managerial judgment, ethical reflection, and contextual awareness.By bridging management theory, functional practice, and critical perspectives, this book fills a critical market gap and is positioned to become the definitive teaching resource on AI and management for business education worldwide.

Artificial Intelligence and the Transformation of Organizations

Algorithmic Management

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

The book explores how emerging digital technologies can address the interconnected challenges of food security, climate change, and sustainability. It delves into AI-driven predictive models for crop yield estimation, IoT-enabled soil and water monitoring, and renewable energy-powered smart irrigation systems. The book highlights practical applications of big data, precision farming, and cloud platforms to enhance productivity, reduce ecological footprints, and improve resilience to climate change. With global case studies and interdisciplinary insights, it serves as a resource for researchers, students, farmers, agribusiness leaders, and policymakers, offering actionable strategies for transforming agriculture into a climate-resilient and resource-efficient sector.

AI, Technology, and Sustainability

Smart Solutions for a Changing Climate

Bridging Technology and Purpose

AI for Financial Sustainability

Security, Audit and Leadership Series

Organizational Debt and AI Failure: Why Your AI Project Fails challenges the assumption that unsuccessful artificial intelligence initiatives are primarily caused by weak models, insufficient computing power, or poor technology choices. Instead, Scott Andersen argues that AI often fails because it is introduced into organizations carrying years of unresolved structural debt.The book presents a practical framework for identifying and managing five interconnected forms of organizational debt: technical, data, personnel, security, and embedded debt. Technical debt creates fragile architectures and brittle integrations. Data debt undermines meaning, lineage, context, and trust. Personnel debt appears through skill gaps, unclear responsibilities, burnout, and dependence on a few critical individuals. Security debt weakens identity, governance, assurance, and accountability. Embedded debt connects them through undocumented assumptions, informal processes, workarounds, and hidden dependencies.AI does not necessarily create these weaknesses-it exposes and accelerates them. Processes that remained stable through human judgment and manual intervention can collapse when automated systems begin operating continuously and at machine speed. What appeared to be resilience may have depended on people quietly compensating for organizational problems.Drawing on decades of enterprise architecture and technology experience, Andersen explains why promising pilots become trapped in "pilot purgatory," why local improvements can increase systemwide risk, and why failures frequently emerge at the seams between technologies, teams, data, and decision authorities. He introduces practical concepts and measures-including Total AI Debt Exposure and Total AI Operational Pressure-to help leaders make risk visible and actionable.This book is written for executives, architects, technology leaders, security professionals, data teams, program managers, and organizations preparing to scale AI. Its central message is direct: successful AI transformation does not begin with adoption. It begins with organizational truth. By identifying, measuring, and governing the debt already present, organizations can move beyond experimentation and build AI systems that achieve delivery, adoption, and sustained operational value.

Why your AI projects fail

Organizational Debt

Emerging Trends in Science, Innovation and Business

"Federated Learning Applications in Healthcare: Empowering Wellness" is an ambitious and timely endeavor aimed at providing a comprehensive exploration of the intersection between federated learning and healthcare.Federated learning, a decentralized machine learning approach that enables model training across multiple devices or institutions without centralized data sharing, holds immense promise for revolutionizing healthcare by facilitating collaboration, preserving patient privacy, and improving healthcare outcomes. This book aims to unravel the complexities of federated learning and demonstrate its transformative potential in various healthcare applications. Through a combination of theoretical insights, practical guidelines, case studies, and real-world examples, the book aims to empower readers to harness the potential of federated learning to address pressing healthcare challenges effectively.Whether readers are healthcare professionals seeking to leverage data-driven approaches to improve patient care, researchers exploring innovative solutions at the intersection of machine learning and healthcare, policymakers grappling with regulatory and ethical considerations, or technologists developing cutting-edge healthcare solutions, this book serves as a valuable resource for understanding, implementing, and advancing federated learning in healthcare.

Empowering Wellness

Federated Learning Applications in Healthcare

The Essential Guide to Launching Your Career in Artificial Intelligence

Break into AI

This book offers an alternate trajectory for EU copyright law. Building on cultural norms in creative communities to reuse, recreate and share, the book proposes a more holistic approach to reconcile conflicting copyright interests. Drawing upon Niklas Luhmann's system theory, John Dewey's theory of art and feminist data theory, it advocates access to, and care within, creative communicative spaces, such as social media platforms or artificial intelligence (AI) data infrastructures, to safeguard creativity and cultural production online. Following a comprehensive assessment of current EU copyright law and related regulation, it proposes a rebuttable presumption of artistic communication to account for the nature of communication between authors, users and the public that safeguards creative reuse. The book isolates the question of remuneration, particularly in AI context, as one of collective socio-cultural value to address wider harms through a cultural commons existing on the border of the EU copyright system. Reflecting on traditional copyright concepts such as authorship, consent and remuneration alongside more novel legal structures like a right of collective informational self-determination, Reshaping EU Copyright Law to Support Creativity Online provides a foundation to reshape how the EU copyright system and its regulatory neighbours adequately respond to new forms of creativity, dissemination, and its use.

Offers an alternate trajectory for EU copyright law to adequately respond to new forms of creativity

Creative Reuse

Reshaping EU Copyright Law to Support Creativity Online

Artificial Intelligence and Blockchain in International Arbitration offers an exhaustive analysis of technology-assisted arbitration across the entire arbitral lifecycle by examining how blockchain and artificial intelligence are used in drafting and concluding arbitral agreements, in the constitution of the tribunal, in the overall procedural management of the case, on evidence and disclosure, on virtual hearings, and even on arbitral award drafting. It delves deeper into the limitations of automation, the non-delegable roles of arbitrators, and the compatibility of digital procedures with core arbitration principles such party autonomy, due process, equality of arms, secrecy, and impartiality. Additionally, it examines how new technologies interact with private international law, with the consent of the parties, the relevant legislation and how these technologies can be incorporated into arbitration without going against public policy, without violation due process rights and, in that way ensuring enforcement under the New York Convention.This book, by examining how blockchain and artificial intelligence are changing arbitral practice, provides a fresh and topical viewpoint on current debates in international arbitration and explores how these technological advancements are reshaping arbitration foundations while posing ethical challenges about the future of arbitration.

Artificial Intelligence and Blockchain in International Arbitration

Innovations in Intelligent Internet of Everything IoE

Biomedical Applications of AI and IoMT in Smart Healthcare

Strategic Insights and Case Studies on Navigating an Entrepreneurial Landscape

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