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Dieses E-Book wurde gemäß der W3C EPUB Accessibility Guidelines oder PDF UA Standards für eine barrierefreie Zugänglichkeit geprüft. Es genügt den Anforderungen an Barrierefreiheit zu Inhaltsstruktur,

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Tim A. Bohlen

Shared Reality

Relational Intelligence as a New Perspective on AI

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

Corporate Governance in the Age of Artificial Intelligence

Contributions to Economics

Pasquale L. Scandizzo holds a Ph.D. from the University of California, Berkeley. He is Professor of Political Economy, past Director and Fellow of the Center for Economic and International Studies, Senior Fellow and Member of the Advisory Board of the University of Rome “Tor Vergata” Foundation, President of the Villa Mondragone Economic Development Association, President Emeritus of the Italian Society of Development Economics, and Chairman of OpenEconomics International, a university spin off focusing on project evaluation and economic development. His former institutional positions include the Governing Board of the Italian Institute of Statistics, the Italian Institute for Economic Planning (President), the National Planning Board, the Italian Parliamentary Budget Committee (Senior Adviser), the Ministry of Economics and Finance (Economic Adviser) the World Bank (Senior Economist and Research Coordinator). He has developed widely published methodologies to evaluate public investment programs, by combining option theory, cost benefit analysis and computable general equilibrium methods, and
 
 has been advising the World Bank and other multilateral institutions on the applications of these methodologies to policies of sustainable development.

This study explores the transformative potential of Artificial Intelligence (AI) in the tourism sector, emphasizing its role in enhancing service quality, operational efficiency, and global reach. To assess future impacts, the study uses a Social Accounting Matrix (SAM) and a Computable General Equilibrium (CGE) model built on GTAP 11 data. A scenario analyzing €66 billion in AI-tourism investments across G7 and other nations suggests strong short-term returns, particularly for capital and skilled labor, with the U.S. leading due to favorable infrastructure and market conditions. These findings point to the need for skill development and equitable policy design. AI’s capacity to personalize experiences and optimize operations positions it as a key driver of sustainable growth in tourism, with considerable economic spillovers and transformative potential across global markets.

A General Equilibrium Analysis

Tourism, Structural Features and Artificial Intelligence

Banking, Money and International Finance

Human-Centred Intelligent Finance

AI, Fintech, and the Future of Global Financial Systems

Artificial intelligence is not just transforming the economy; it is fundamentally redefining the core principles of economic theory.
From the Phillips Curve to portfolio optimization, and from the Laffer Curve to Lewis’s dual-sector model, the core frameworks that have shaped economics for over a century are now evolving through intelligent machines, algorithms, and data-driven decision-making. In this work, Tshilidzi Marwala reanalyzes 18 fundamental principles of economic thought, such as demand and supply, rational choice, information asymmetry, mechanism design, agency theory, comparative advantage, growth, governance, and market efficiency, from an AI perspective.
Drawing on economics, artificial intelligence, finance, public policy, and global governance, the book explains how AI is changing productivity, labor markets, inflation, competition, taxation, and the relationships between states, companies, and citizens. It shows that traditional ideas based on scarcity, human labor, limited rationality, and static institutions are gradually being replaced by a modern economic framework driven by intelligent capital, algorithmic coordination, and autonomous systems. The outcome is a comprehensive and timely framework for understanding the political economy of the AI era, detailed in analysis, globally oriented, and essential for policymakers, scholars, business leaders, and anyone seeking to understand how intelligence is becoming the primary driver of economic transformation.

Artificial intelligence is not just transforming the economy; it is fundamentally redefining the core principles of economic theory.From the Phillips Curve to portfolio optimization, and from the Laffer Curve to Lewis’s dual-sector model, the core frameworks that have shaped economics for over a century are now evolving through intelligent machines, algorithms, and data-driven decision-making. In this work, Tshilidzi Marwala reanalyzes 18 fundamental principles of economic thought, such as demand and supply, rational choice, information asymmetry, mechanism design, agency theory, comparative advantage, growth, governance, and market efficiency, from an AI perspective.
 Drawing on economics, artificial intelligence, finance, public policy, and global governance, the book explains how AI is changing productivity, labor markets, inflation, competition, taxation, and the relationships between states, companies, and citizens. It shows that traditional ideas based on scarcity, human labor, limited rationality, and static institutions are gradually being replaced by a modern economic framework driven by intelligent capital, algorithmic coordination, and autonomous systems.
 
 The outcome is a comprehensive and timely framework for understanding the political economy of the AI era, detailed in analysis, globally oriented, and essential for policymakers, scholars, business leaders, and anyone seeking to understand how intelligence is becoming the primary driver of economic transformation.

How AI Rewrites Theory, Markets, and Policy

Intelligent Economies

Wiley Finance

The handbook to unleash the power of AI in Finance with guidance to pragmatically managing AI Risk Are you ready to harness the transformative potential of artificial intelligence and machine learning in finance while effectively managing the associated risks? "AI and Risk Management in Finance: A Practitioner's Handbook" by Sri Krishnamurthy, CFA, is your indispensable guide. Tailored for financial professionals, this comprehensive handbook delivers practical insights, case studies, and frameworks to navigate the complex landscape of AI and ML in the financial sector. This pragmatic handbook, developed primarily for professionals involved in designing, developing, and deploying AI models in the financial industry explores cutting-edge technologies, regulatory landscapes, and pragmatic frameworks. From generative AI to robust risk management strategies, this handbook equips you with the tools you need to validate models, ensure compliance, and operationalize AI risk management effectively. Leveraging lessons from QuantUniversity's AI and Machine Learning Risk Management program offered in 18 countries, this book focuses on enabling practitioners apply the state-of-the-art AI and machine learning techniques factoring unique risks specific to the financial services domain. Whether you're a seasoned professional or a newcomer, this book offers invaluable insights for harnessing the power of AI responsibly in the financial industry. Highlights of the Book: <ul> <li>Machine Learning and AI in Financial Services: Dive into the fundamentals of ML and AI, exploring various applications within the financial industry through real-world case studies.</li> <li>Generative AI and LLMs in Finance: Understand the emerging landscape, key players, and advanced concepts like prompt engineering and fine-tuning with practical examples.</li> <li>Risk Management for AI/ML Applications: Learn about current and emerging regulatory landscapes, AI risk management frameworks, and legislative efforts shaping the field.</li> <li>Data Governance Issues: Address critical aspects of data quality, privacy, security, and governance, with actionable frameworks and illustrative case studies.</li> <li>Model and System Governance: Gain insights into validating machine learning models, quantifying model risk, and ensuring robust system governance with MLOps and model monitoring.</li> <li>Key Risk Assessment Facets: Focus on documentation, explainability, fairness, security, and reliability with detailed case studies.</li> <li>Verification and Validation: Distinguish between verification and validation and learn frameworks for effective AI application validation.</li> <li>Algorithmic Auditing: Conduct comprehensive algorithmic audits with detailed processes and real-world examples.</li> <li>Operationalizing AI Risk Management: Discover ten essential strategies for implementing AI risk management practices effectively in your organization.</li> </ul> Prepare for the future of finance with expert advice and actionable strategies. Don't miss out on this comprehensive guide-your roadmap to navigating AI and risk management in the financial sector.

A Practitioner's Guide to Machine Learning, Generative AI, Agentic Systems, and Responsible Deployment

AI and Risk Management in Finance

Innovations in Intelligent Internet of Everything IoE

Biomedical Applications of AI and IoMT in Smart Healthcare

'Book of the Year' as chosen by The Conversation'Disconcerting . . . a disturbing and important book' NEW SCIENTIST'Smart and wonderfully readable' NEW YORK TIMESThe bad science and sinister ideas behind Silicon Valley's foolish obsession with immortality, AI paradise and limitless growth.Tech billionaires have decided that they should determine our futures for us. According to Elon Musk, Jeff Bezos, Sam Altman and more, the only good future for humanity is one powered by technology: trillions of humans living in space, functionally immortal, served by superintelligent AIs.In More Everything Forever, scientist and writer Adam Becker investigates these wildly implausible and often profoundly immoral visions of tomorrow to reveal why, in reality, there is no good evidence that they will, or should, come to pass. The giants of Silicon Valley claim that their ideas are based on science, but the truth is darker: they come from a jumbled mix of shallow futurism and racist pseudoscience. And behind these fanciful visions of space colonies and digital immortality is a cynical power grab, at the expense of essential work spent on solving real problems like the climate crisis.More Everything Forever exposes the powerful myths that dominate Silicon Valley, challenging us to see how foolish, and dangerous, these visions of the future are.

AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity

More Everything Forever

Turn enterprise AI into a source of strategic insight, not just productivity gains.The AI Gap by leading AI expert and keynote speaker Richard Foster-Fletcher shows business and technology leaders how to unlock greater value from enterprise AI by changing the structures, processes and culture surrounding it. Organizations invest in AI expecting new intelligence and transformative insights. Yet AI is often introduced through procurement, security, legal and compliance systems designed for standard software, restricting its potential before it can deliver on that promise. This book explains why this gap persists and what organizations must change to close it. You'll learn how to: - Identify organizational barriers limiting the value of AI - Move beyond productivity-focused AI implementation - Create conditions where AI can generate deeper insights - Enable employees to explore, experiment and challenge established thinking &gt;The AI Gap equips leaders to rethink AI implementation, create space for experimentation and turn artificial intelligence into a powerful driver of organizational insight and long-term business value. Themes include: enterprise AI, AI implementation, AI strategy, business transformation, organizational culture, AI innovation

How Business Decisions Expand What AI Can Do

The AI Gap

This book provides a state-of-the art picture of the transformation of the global legal market. The traditional business model of law firms has been upended by new forms of organisation, often (but not exclusively) brought about by technological innovation and the use of technology for the execution of legal activities, which implies the so-called 'servitisation' of the legal market. Such trends raise a broad range of questions of both practical and academic nature, which the book tackles extensively, relying on the competence of a remarkable group of experts, coming from different professional backgrounds and knowledgeable of many different jurisdictions, from Europe to the USA, from Asia to Australia. In particular, the book has three main focuses: 1) a law and economics analysis of today's legal market, combined with a description of how regulatory changes have had an impact on competition in the legal services business, and on the evolution of this industry; 2) a thorough investigation of the impact of technological disruptions on the legal services industry, considering how legal tech companies and artificial intelligence solutions are reshaping the activities of legal professionals and the legal market more broadly; 3) a survey of the "new lawyers" and other new legal professionals, along with a reflection on the reforms needed to align their education with market needs.The book caters to all those interested, professionally or academically, in keeping track of the evolution of the legal services market. Practising lawyers who want to be "future-proof", law students, new specialised legal professionals active in the business and financial sectors, scholars and other researchers (both lawyers and economists) conducting research in the field, as well as anyone engaged in providing legal education, will find in this book extremely valuable insights on current trends and future developments in the legal market.

How Innovation, Legal Tech and AI Have Been Reshaping the Legal Market

Future-Proof Legal Services

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

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

Shared Reality

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