KI ist ein weltweiter Megatrend. Bedeutung, Leistung und Komplexität von KI-Lösungen nehmen rasant zu und daher wächst auch der Bedarf, einen Überblick über die relevanten KI-Lösungen zu behalten und die damit verbundenen Prioritäten und Risiken zu managen. Das vorgestellte AI Methods, Capabilities and Criticality Grid (AI-MC2-Grid) stellt eine Methode und ein Werkzeug dar, um diesen Überblick zu gewinnen und die KI-Lösungen zu verwalten. Nutzer des AI-MC2-Grid können Manager, Entwickler und Anwender von KI-Lösungen sein, aber auch Investoren, Politiker und Regelsetzer, die den Markt verstehen und bestimmte KI-Lösungen verwalten wollen.Das AI-MC2-Grid besteht aus drei Dimensionen: KI-Methoden, KI-Fähigkeiten und die Kritikalität einer KI-Lösung. Jede diskutierte KI-Lösung kann in diese drei Dimensionen eingeordnet werden, so dass ähnliche KI-Lösungen verglichen werden können. Alternativ können komplexe KI-Lösungen anhand ihrer Komponenten analysiert werden. KI-Methoden entsprechen dabei typischen KI-Algorithmen, während KI-Fähigkeiten typischen Prozessschritten zum Aufbau intelligenter Workflows beschreiben. Sind die relevanten KI-Methoden und KI-Fähigkeiten einer bestimmten KI-Lösung gefunden, können Leistung, Folgen und mögliche Risiken und Alternativen diskutiert werden. Basierend auf der Klassifizierung stellt das Schadenspotenzial von Künstlicher Intelligenz eine bestimmte Stufe der Kritikalität dar. In diesem Zuge steigen mit zunehmender Kritikalität auch die Anforderungen an Tests, Kalibrierung, Inspektion, Kontrolle und Zertifizierung. Das AI-MC2-Grid eine leistungsfähige Methode und ein Werkzeug, um alle Arten von kommenden Normen und Standards von KI-Lösungen zu definieren und zu verwalten.Aus diesem guten Grund steht das AI-MC2-Grid im Mittelpunkt der Deutschen Normungsroadmap für Künstlichen Intelligenz, die als Werkzeug zur Unterstützung der Entwicklung und des Managements zukünftiger KI-Standards und -Normen

Understand how to adopt and implement AI in your organization Key Features _ 7 Principles of an AI Journey _ The TUSCANE Approach to Become Data Ready _ The FAB-4 Model to Choose the Right AI Solution _ Major AI Techniques & their Applications: - CART & Ensemble Learning - Clustering, Association Rules & Search - Reinforcement Learning - Natural Language Processing - Image Recognition Description Most AI initiatives in organizations fail today not because of a lack of good AI solutions, but because of a lack of understanding of AI among its end users, decision makers and investors. Today, organizations need managers who can leverage AI to solve business problems and provide a competitive advantage. This book is designed to enable you to fill that need, and create an edge for your career. The chapters offer unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations. By the end of the book, you will be ready to offer any organization the capability to use AI successfully and responsibly - a need that is fast becoming a necessity. What will you learn _ Understand the major AI techniques & how they are used in business. _ Determine which AI technique(s) can solve your business problem. _ Decide whether to build or buy an AI solution. _ Estimate the financial value of an AI solution or company. _ Frame a robust policy to guide the responsible use of AI. Who this book is for This book is for Executives, Managers and Students on both Business and Technical teams who would like to use Artificial Intelligence effectively to solve business problems or get an edge in their careers. Table of Contents 1.Preface 2.Acknowledgement 3.About the Author 4.Section 1: Beginning an AI Journey a. AI Fundamentals b. 7 Principles of an AI Journey c. Getting Ready to Use AI 5.Section 2: Choosing the Right AI Techniques a. Inside the AI Laboratory b. How AI Predicts Values & Categories c. How AI Understands and Predicts Behaviors & Scenarios d. How AI Communicates & Learns from Mistakes e. How AI Starts to Think Like Humans 6.Section 3: Using AI Successfully & Responsibly a. AI Adoption & Valuation b. AI Strategy, Policy & Risk Management 7.Epilogue

Artificial Intelligence (AI) will change the lives of people and businesses more fundamentally than many people can even imagine today. This book illustrates the importance of AI in an era of digitalization. It introduces the foundations of AI and explains its benefits and challenges for companies and entire industries. In this regard, AI is approached not just as yet another technology, but as a fundamental innovation, which will spread into all areas of the economy and life, and will disrupt business processes and business models in the years to come. In turn, the book assesses the potential that AI holds, and clarifies the framework that is necessary for pursuing a responsible approach to AI. In a series of best-practice cases, the book subsequently highlights a broad range of sectors and industries, from production to services; from customer service to marketing and sales; and in industries like retail, health care, energy, transportation and many more. In closing, a dedicated chapter outlines a roadmap for a specific corporate AI journey. No one can ignore intensive work with AI today - neither as a private person, let alone as a top performer in companies. This book offers a thorough, carefully crafted, and easy to understand entry into the field of AI. The central terms used in the AI ​​context are given a very good explanation. In addition, a number of cases show what AI can do today and where the journey is heading. An important book that you should not miss! Professor Dr. Harley Krohmer University of Bern "Inspiring, thought provoking and comprehensive, this book is wittingly designed to be a catalyst for your individual and corporate AI journey.” Avo Schönbohm, Professor at the Berlin School of Economics and Law, Enterprise Game Designer at LUDEO and Business Punk

How can startups successfully scale customer acquisition and revenue growth with a Lean team? Out-of-the-box acquisition solutions from Facebook, Google, and others provide a good start, but the companies that can tailor those solutions to meet their specific needs, objectives, and goals will come out winners. But that hasn’t been an easy task—until now. With this practical book, author Lomit Patel shows you how to use AI and automation to provide an operational layer atop those acquisition solutions to deliver amazing results for your company. You’ll learn how to adapt, customize, and personalize cross-channel user journeys to help your company attract and retain customers—to usher in the new age of Autonomous Marketing. Learn how AI and automation can support the customer acquisition efforts of a Lean Startup Dive into Customer Acquisition 3.0, an initiative for gaining and retaining customers Explore ways to use AI for marketing purposes Understand the key metrics for determining the growth of your startup Determine the right strategy to foster user acquisition in your company Manage the increased complexity and risk inherent in AI projects

Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.

This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.

Knowledge Management: Systems and Processes in the AI Era, Third Edition, is aimed at students and managers who seek detailed insights into contemporary knowledge management (KM). It explains the concepts, theories, and technologies that provide the foundation for knowledge management; the systems and structures that constitute KM solutions; and the processes for developing, deploying, and evaluating these KM solutions. This book serves as a complete introduction to the subject of knowledge management, incorporating technical and social aspects, as well as concepts, practical examples, traditional KM approaches, and emerging topics. This third edition has been revised and expanded to include more coverage of emergent trends such as cloud computing, online communities, crowdsourcing, and artificial intelligence. Aimed at advanced undergraduate, postgraduate, and MBA students who are seeking a comprehensive perspective on knowledge management, Knowledge Management is also complemented by online support for lecturers including suggested solutions to the many review questions and application exercises contained within the book.