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Strategic Insights and Case Studies on
Navigating an Entrepreneurial Landscape

Strategic Insights and Case Studies on Navigating an Entrepreneurial Landscape

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

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

Leveraging Data Science and Machine Learning

Predictive Intelligence for Transforming Healthcare Insurance

An Integrated Approach to Uncertainty

Strategic Decision-Making

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

Decision-Making in the Age of Artificial Intelligence

Do We Still Need to Decide?

A step-by-step guide to AI-native analytics systems for BI practitioners Building Business Intelligence Apps with AI provides a step-by-step guide for data analysts, data engineers, and BI developers who need to integrate AI into their analytics workflows. Written by Ryan Dolley, a data industry veteran with fifteen years of experience across BI development, consulting, and data vendor roles, this book shows how to partner with AI to deliver better data models, dashboards, and business queries while building AI-native experiences for end users. The book addresses data foundations, outsourcing repetitive tasks to AI, and scaling autonomous analytics systems that maintain accuracy and data governance. Readers learn practical steps for increasing individual and team effectiveness using AI while avoiding common pitfalls such as hallucination, data inaccuracy, and user abandonment. It delivers operating models that data departments need, covering everything from data blending and dashboard creation to personalization and responsiveness. Readers will also find: <ul> <li>Practical techniques for partnering with LLMs to accelerate data modeling, querying, and dashboard development across BI workflows</li> <li>Strategies to outsource repetitive analytics tasks to AI while maintaining rigorous data governance and accuracy standards</li> <li>Operating models for individuals and data departments to scale AI-native analytics systems that end users adopt</li> <li>Methods for building autonomous, personalized analytics experiences that address user expectations for speed and responsiveness</li> <li>Guidance on avoiding AI pitfalls including hallucination, data inaccuracy, and user abandonment in production analytics environments</li> </ul> Data analysts, data engineers, BI developers, and their managers will find in this book the specific skills and operating models needed to integrate AI into daily analytics work. It equips practitioners to build accurate, autonomous analytics systems while strengthening data governance and accelerating delivery across their teams.

Building Business Intelligence Apps with AI

Design AI systems that teach your workforce instead of replacing it The Resilient Enterprise: Designing Artificial Intelligence that Teaches the Workforce draws on cognitive psychology and UX principles to show business leaders how to deploy AI that strengthens employee competence rather than eroding it. Victor S. Yocco, PhD, a Staff UX Researcher at ServiceNow with over a decade directing product design research at EY, delivers specific pedagogical design patterns that leaders can implement immediately to counter skill atrophy caused by AI overreliance. The World Economic Forum identifies skill atrophy as a top concern for Chief People Officers due to AI overreliance. This book directly addresses that risk by providing actionable frameworks for designing AI-powered tools and agents that preserve structural knowledge across junior and senior staff. It connects cognitive psychology research to practical interface design, equipping leaders with methods to build organizations where humans and machines both perform at their highest capability. Readers will also find: <ul> <li>Pedagogical design patterns for AI interfaces that reinforce rather than replace employee reasoning and decision-making skills</li> <li>Strategies for preventing cognitive skill atrophy among senior staff whose expertise is being offloaded to AI-powered automation</li> <li>Approaches to ensure junior employees develop the structural knowledge required for their roles alongside AI tools</li> <li>UX principles grounded in cognitive psychology that guide how AI agents should interact with human workers</li> <li>Frameworks for building organizational resilience so teams can function effectively both with and without AI assistance</li> </ul> Written for Chief People Officers, Chief Information Officers, Vice Presidents of Product Management, Directors of Learning and Development, and Senior Managers of Operations, this book provides the pedagogical design patterns and cognitive frameworks needed to deploy AI that preserves and strengthens workforce expertise rather than undermining it.

Designing Artificial Intelligence that Teaches the Workforce

The Resilient Enterprise

When to Take the Long Road in a Shortcut World

ASAP: As SLOW as Possible

**This edition will be released in March 2027. If you want to get a copy ahead of then, have a look at our hardback edition, released in May 2026.** 'If you're worried about wasting your life, read this book.' Rutger Bregman, author of Humankind A ridiculously in-depth guide to finding a fulfilling and impactful career in an age of AI. You have about 80,000 hours in your career: 40 hours a week, 50 weeks a year, for 40 years. This means your choice of career is the most important decision you'll ever make. Choose well, and you can have a more rewarding, interesting life, and also help solve some of the world's most pressing problems. Choose poorly, and you could waste decades. So what should you do? Most advice is based on no research, instead offering (misleading) platitudes like 'follow your passion'. It's surprisingly out of date, focusing on traditional paths rather than those most likely to thrive in an age of AI. And if you want to help others, the advice is even more simplistic: telling you to choose careers like nurse or doctor, when there are paths in which almost anyone can save more lives. In fact, some careers have hundreds of times more impact than others, but most of us have no idea which ones. Benjamin Todd is the founder of 80,000 Hours, a non-profit that's spent over ten years researching how to have a meaningful and impactful career. Here he introduces a tried-and-tested toolkit framework that has already led thousands of people to change their path. It covers:<ul><li>What really makes for a dream job, and why finding it probably doesn't involve 'following your passion'.</li><li>How to identify which global problems are most pressing, and why they might involve AI as much as climate change.</li><li>Which roles are likely to be automated, and how to ensure yours isn't among them.</li></ul> It's also full of practical tips and tools. You'll come away with a plan to use your 80,000 hours in a way that's rewarding and fulfils your potential to make a difference. 'This career guide is among the most thoughtful and grounded I've seen.' Cal Newport, author of Deep Work 'A remarkably rigorous guide about how to find that perfect career for you.' Ali Abdaal, author of Feel-Good Productivity 'Based on evidence and good sense, not platitudes.' Steven Pinker, author of The Better Angels of our Nature 'The most informative book you can read if you're stuck trying to make one of life's most important decisions.' Hannah Ritchie, author of Not the End of the World

How to Have a Fulfilling Career That Does Good

80,000 Hours

Taylor and Francis Proceedings in Computer Science and Engineering

Reimagining Tomorrow: AI and Sustainable Imperative presents a curated collection of high-quality research contributions that explore the transformative role of Artificial Intelligence in addressing pressing sustainability challenges across a variety of sectors.This book highlights how advanced AI techniques-ranging from machine learning and deep learning to intelligent optimization-are being leveraged to enhance efficiency, reduce environmental impact, and support data-driven decision-making. The volume emphasises the growing importance of integrating technological innovation with sustainability goals to create resilient and future-ready systems. The primary focus of this book is on human-centred Artificial Intelligence, with particular attention given to its ethical, societal, and governance dimensions. It examines critical issues such as transparency, fairness, accountability, and privacy, while also showcasing AI-driven solutions for sustainable development in key domains, including healthcare, education, smart infrastructure, and Industry 5.0. The contributions further address interdisciplinary approaches, combining AI with emerging paradigms such as edge computing, IoT, and green technologies to enable scalable and responsible innovation.The book provides valuable insights for researchers, academicians, industry practitioners, policymakers, and students by offering a comprehensive perspective on both theoretical advancements and practical implementations of AI for sustainability and serves as a reference for understanding current trends, identifying research gaps, and exploring future directions in the design of intelligent, ethical, and sustainable systems.

AI and Sustainable Imperative

Reimagining Tomorrow

Strategic Insights and Case Studies on Navigating an Entrepreneurial Landscape

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