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Navigating the Self-Service Revolution
With Smart Machines

Navigating the Self-Service Revolution With Smart Machines

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

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

Banking, Money and International Finance

Human-Centred Intelligent Finance

AI, Fintech, and the Future of Global Financial Systems

Advances in Science, Technology & Innovation

This book explores the dynamic intersection of digital technologies, artificial intelligence (AI), and their applications across two key business areas: customer loyalty and employee performance. The first part discusses the evolving role of marketing in building customer relationships, with a specific focus on how AI, data analytics, and digital influencers are reshaping consumer behaviors and brand interactions. From optimizing customer engagement through AI and chatbots to the dark side of AI’s influence on consumer trust, this section offers a critical examination of modern marketing trends. The second part of the book shifts toward the integration of AI and digital human resource (HR) strategies to enhance employee well-being and organizational performance. Topics such as gamification, HR analytics, and the role of AI in improving workforce efficiency are discussed, alongside emerging trends like industry 5.0’s impact on HR practices and employee satisfaction. This book provides crucial insights into how businesses can leverage AI-driven solutions not only to retain customers but also to optimize their internal workforce and create sustainable growth.

Marketing and Workforce-Based AI Strategies

Artificial Intelligence and the Transformation of Organizations

Algorithmic Management

A Socially Embedded Theory of Memory‑Driven Consumption

Nostalgia and Consumer Behavior

Tech, War and the Fight for Humanity

Thundercloud

Hart Studies in Commercial and Financial Law

This book provides a commentary on the Markets in Crypto-Assets Regulation (MiCAR), a game-changing EU regulation for crypto-assets and crypto-asset services. Directly applicable in all EU Member States, MiCAR serves as a benchmark for future regulation in other jurisdictions, influencing rulemaking and crypto industry around the world. In this book, leading experts in the fields of financial law, regulation and technology examine the goals, rules and operation of MiCAR. The book explores its provisions in the broader context of current market practices, technological developments, existing financial law instruments (eg MiFID II, Prospectus Regulation, Crowdfunding Regulation and Market Abuse Regulation), court cases (eg the bankruptcies of FTX and Celsius), regulatory initiatives in the USA and the UK, as well as soft law instruments. The book is designed for anyone dealing with crypto-assets or considering entering the crypto space. This includes representatives from legal and business communities, both incumbent (banks, investment firms, investment funds) and new market players (crypto exchanges, wallet service providers, issuers of stablecoins), supervisory authorities, students and academics. The reader will gain a deep understanding of the scope and structure of MiCAR, key terms used in it, its rationale, and the main rules for issuers of crypto-assets, crypto-asset service providers and crypto-asset services.

Law and Technology

Markets in Crypto-Assets Regulation

Artificial intelligence has crossed the liability Rubicon. It is no longer a backend IT experiment governed by soft ethics, voluntary frameworks, and vague policy statements; it is a material financial asset driving enterprise revenue and unprecedented legal exposure. As we transition into Industry 5.0, algorithms are making autonomous, consequential decisions at machine speed. Yet, corporate boards and risk committees are attempting to govern these gigahertz systems using static compliance checklists designed for a slower, simpler era. The result is a looming crisis of algorithmic discrimination, regulatory friction, and catastrophic reputational decay. When an opaque, black-box model hallucinates financial advice or leaks proprietary trade secrets, the ensuing failure cascade can destroy billions in market capitalization overnight.AI Governance and Risk Management provides the definitive, boardroom-ready blueprint for surviving the fragmented global regulatory dragnet. This book dismantles the illusion of traditional "Human-in-the-Loop" oversight, proving that true algorithmic safety requires hard, architectural constraints. Drawing on decades of technology operations and academic leadership, the text translates classical financial auditing principles into executable machine logic. The author brings unparalleled practical experience-from supporting six Silicon Valley startups in client-facing roles to develop computer vision use cases, to leading over 30 continuous improvement projects for Cisco Systems. Having authored foundational texts on Segregation of Duties (SOD) and Hierarchical SOD two decades ago, and backed by 15 years of teaching financial risk management, this expertise culminates in the AI Integrity Framework (AIIF). This Hamiltonian approach empowers organizations to embed continuous improvement cycles and strict SOD directly into their deployment pipelines.Readers will discover how to engineer automated "Build Breaks," architect deterministic kill switches, and secure the unstructured data supply chain against copyright contamination and intellectual property theft. By shifting from reactive public relations to proactive "Governance as Code," Chief Risk Officers, legal counsel, and audit committees can mathematically prove fiduciary control to regulators across overlapping jurisdictions, from California to the European Union.Authored by a veteran industry practitioner, creator of five previous Wiley &amp; Sons texts, and current developer of the Industry 5.0 and AI curriculum at Santa Clara University, this release is not a theoretical ethics manual. It is an uncompromising operational survival guide. It provides the exact structural tools necessary to transform artificial intelligence from an unquantified off-balance-sheet liability into a fully auditable, legally defensible, and highly profitable enterprise asset.

The AI Integrity Framework (AIIF) for Enterprise Control and Regulatory Compliance

Auditable AI Governance and Risk Management

Agritech

Digitalisation and Artificial Intelligence in Agritech and Food Supply Chains, Volume I

Navigating the Self-Service Revolution With Smart Machines

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