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Swearingen K: The Capability Debt

The Capability Debt

Why AI is Exposing What Organizations Never Built

Risk, Governance and Society

From Data Analytics to Global Risk Governance

Evolution of Anomaly Detection

Das vorliegende Buch gibt einen kompakten Einblick in die Gemeinwohl-Ökonomie (GWÖ). Die GWÖ stellt ein Instrumentarium zur Leistungsermittlung von Unternehmen und Gemeinden zur Verfügung, das von Nachhaltigkeitsaspekten geprägt ist und mit den Sustainable Development Goals (SDGs) gut harmoniert. Die GWÖ hat nachweislich das Potenzial für positive Veränderung im Sinn einer erforderlichen Wirtschaftstransformation.

Baustein einer Wirtschafts- und Gesellschaftstransformation

Gemeinwohl-Ökonomie (GWÖ)

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

Computers, Privacy and Data Protection

Who decides how data and AI are governed, and whose rights prevail?This open access book brings together contributions from the CPDP conference in Brussels, Europe's leading forum on privacy and data protection. Ten years after the GDPR, digital governance stands at a crossroads. The EU has layered the DSA, DMA, Data Act and AI Act onto its data protection regime, while calls for simplification grow louder and governments from Brazil and Mexico to Canada and Southeast Asia pursue their own regulatory visions. The book examines algorithmic oversight and automated decision-making in the UK, AI and directors' duties in Canadian corporate law, data governance for connected vehicles in the EU, GDPR-inspired access rights across Japan and Southeast Asia, the Brussels Effect in Brazil and Mexico, location-data provenance and digital trust infrastructures, and the inequalities produced by biometric and health data infrastructures in Europe and India.The chapters show that governance failures rarely stem from a shortage of rules. They arise when regulatory visions, technical architectures and institutions pull in different directions. Read together, they make the case for treating disagreement not as an obstacle but as a democratic resource.With its blend of doctrinal analysis, critical theory and socio-technical insight, this book is for academics, policymakers, practitioners, DPOs and students working on data protection, AI regulation and digital society.The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com.

Competing Visions, Shared Futures

Data Protection, Privacy and Artificial Intelligence, Volume 19

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI, and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact.Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments.You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behaviorFeaturing real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance.Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

The Strategy, Governance, and Economics of Agentic AI

Building an Agentic Organization

Lecture Notes in Operations Research

Proceedings of 2026 INFORMS Conference on Service Science, Hangzhou, China, May 30 - June 1, 2026

Weaving the World with Digitalization and AI

Turn Intelligence into Your Competitive Advantage

Enterprise 5.0

Agentic AI - The Director's Governance Handbook: Risk, Accountability and Board Oversight addresses the most significant governance challenge currently facing boards: the deployment of autonomous AI systems that act, decide, and affect the interests of customers, counterparties, and regulators without human approval of each specific action. The book is written for independent directors, board committee members, and governance practitioners who need governance literacy rather than technical expertise - the ability to ask the right governance questions, evaluate management's answers, and discharge the duty of care that the Companies Act and India's evolving AI regulatory landscape require.

Risk, Accountability and Board Oversight

Agentic AI - The Director's Governance Handbook

Professional Practice in Governance and Public Organizations

This book examines how governance structures shape incentives, behavior, and long-term investment, arguing that the quality of governance is the primary determinant of prosperity and liberty. It explains how political power operates, why inclusive democracies tend to outperform autocracies, and how institutional frameworks can leverage technology to automate enforcement.&nbsp;Drawing on institutional economics, mechanism design, game theory, and systems engineering, the book reframes constitutional design as an engineering problem rather than an ideological debate. Instead of prescribing specific policy decisions, it proposes a framework for constructing rules and constitutional provisions that reliably produce better collective decisions.&nbsp;Moving from theory to practice, the book offers a rigorous blueprint for scholars, policymakers, reformers, and technologists seeking to improve governance. It provides concrete tools for institutional reform, including an AI-based adjudication system and a “smart constitution” deployable on a blockchain to govern political transitions and establish legitimate interim governments. It also proposes a zero-trust constitutional framework that assumes adversarial behavior by public officials.&nbsp;

From Theories to Codes

Better Governance

The evolution of AI isn’t just about predictive models and automation; it’s about the emergence of "agentic" capabilities—autonomous and specialized AI systems that operate with a sense of independence by acting on a user’s behalf. This book explores through dialogue between the authors, the transformative role of AI in modern organizations, beginning with its evolution from automation to augmentation and the paradigm shift in human-machine collaboration.

The book starts with Microsoft's AI ecosystem, showcasing tools like Copilot, Power Platform, Dynamics 365, and Azure AI that enable AI agentic solutions. It further emphasizes responsible AI implementation, covering ethical guidelines, risk mitigation, and security measures with a specific focus on agentic systems. Finally, it provides a roadmap for businesses and professionals to adapt to an agentic workforce, measuring AI’s impact while preparing for future breakthroughs. 

After reading this book, you will be able to leverage agentic systems at scale and also address the implications of using agentic AI responsibly.

What You Will Learn:

The foundations of "agency" in AI

Practical strategies for implementing agentic AI solutions using Microsoft’s ecosystem

Best practices in Responsible AI, ethical considerations, and risk mitigation for autonomous agents

Actionable next steps for embracing agentic AI in day-to-day work and broader AI transformation efforts




Who This Book Is For:

AI engineers, Business Analysts, and enterprise architects curious about specialized AI strategies

Leveraging Microsoft AI and Autonomous Agents to Transform Work and Business

The Agentic AI Revolution

Implement trusted AI systems that deliver measurable business value while managing risk, compliance and long-term performance. Decision-Quality AI by Eva-Marie Muller-Stuler is a practical guide for data, product and technology leaders responsible for turning AI ambition into real-world outcomes. Covering the complete AI lifecycle from strategy and team design to deployment and governance, it provides the frameworks and technical foundations needed to develop AI products that are effective, responsible and aligned with business goals. Designed for leaders implementing AI at scale, this book helps you move beyond experimentation and hype to build AI solutions that solve genuine business challenges while meeting regulatory and operational requirements. You will learn how to: - Define AI use cases that address real business needs - Build teams, processes and governance for AI delivery - Develop, test and deploy AI with confidence - Manage risk, compliance, security and transparency - Monitor performance throughout the AI lifecycle Decision-Quality AI combines responsible AI principles with the practical disciplines required for successful implementation. It explores areas such as MLOps, ModelOps, AIOps, DevSecOps and cybersecurity, giving you a complete framework for delivering AI that creates lasting impact. Whether you are launching your first AI initiative or scaling enterprise-wide adoption, this book provides the tools, processes, and leadership guidance you need to build trusted AI systems that deliver results. Themes include: AI development, AI governance, AI security, MLOps, ModelOps, risk management, DevSecOps, data architecture, AI strategy

Grasp how to deliver fully deployed, scalable, trusted and useful AI and avoid expensive failed solutions and limited proof-of-concepts with this practical guide covering the lifecycle of AI development.

From AI Ambition to Operational Success

Decision-Quality AI

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

The Capability Debt

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