Artificial Intelligence For Sustainable Value Creation

Artificial Intelligence for Sustainable Value Creation provides a detailed and insightful exploration of both the possibilities and the challenges that accompany widespread Artificial Intelligence

A hyperconnected, constantly evolving world has emerged. A world where people (internet of people), things (internet of things), and data (internet of data) are linked together, shaping the global economy while demanding new, innovative approaches for value creation. The era of hyper-connectivity is no longer characterized by centralized firm-centric business structures and traditional intra-firm and inter-firm processes. Open, distributed ecosystemic formations have started to emerge, utilizing cutting edge technologies to harness the collective power, co-creation ability, and intelligence of the crowd, the data, and the environment in an open participatory value co-creation mode. However, the question has become whether the frameworks, models, and tools that organizations use to create value will remain the same in the new business environment and within the organizations themselves. Existing literature on ecosystems, business models, and business model innovation are starting to examine these aspects. Emerging Ecosystem-Centric Business Models for Sustainable Value Creation explores emerging technology-enabled ecosystems and ecosystem-centric business models in theory and practice, from a business and technological perspective, and in a range of industrial settings, aiming to contribute to the existing knowledge of innovative technology-advanced ecosystems and business models, facilitating their design, implementation, and sustainable value creation. It examines the dynamics of this technology-powered revolution and how it is influencing the foundations of value creation and business modeling in novel ecosystemic formations across the HMD triangle: human, machine, and data. The target audience of this book is researchers and professionals in the fields of innovation, business, and strategy as well as computer science and information technology, along with managers, executives, practitioners, researchers, academicians, and students interested in new ways to create value in emerging and future ecosystems via innovative ecosystem-centric business models and strategies.

This book states that data users often suffer from the difficulty of acquiring knowledge for decision-making, and others are unsure how existing data are useful. The reader will be released from these dilemmas and enabled to act beyond patterns in past events by creating a process to interact with the data market and the dynamic real-world rich in new events. We present new approaches from the aspects of computation, communication, and their integration, to readers including analysts in sciences and businesses, systems managers, and learners desiring to design knowledge to learn. We show clues to explaining causalities in the target world of a black-box AI of which users may seek a predictive performance. For obtaining interpretable knowledge, we show the integration of model- and data-driven approaches, the analysis and perception of signals from data acquired in the cyber or the real word, and creative communication which connects demands to data by visualizing the data market as a place for innovations

Unlock unprecedented levels of value at your firm by implementing artificial intelligence In The Secrets of AI Value Creation: Practical Guide to Business Value Creation with Artificial Intelligence from Strategy to Execution, a team of renowned artificial intelligence leaders and experts delivers an insightful blueprint for unlocking the value of AI in your company. This book presents a comprehensive framework that can be applied to your organisation, exploring the value drivers and challenges you might face throughout your AI journey. You will uncover effective strategies and tactics utilised by successful artificial intelligence (AI) achievers to propel business growth. In the book, you’ll explore critical value drivers and key capabilities that will determine the success or failure of your company’s AI initiatives. The authors examine the subject from multiple perspectives, including business, technology, data, algorithmics, and psychology. Organized into four parts and fourteen insightful chapters, the book includes: Concrete examples and real-world case studies illustrating the practical impact of the ideas discussed within Best practices used and common challenges encountered when first incorporating AI into your company’s operations A comprehensive framework you can use to navigate the complexities of AI implementation and value creation An indispensable blueprint for artificial intelligence implementation at your organisation, The Secrets of AI Value Creation is a can’t-miss resource for managers, executives, directors, entrepreneurs, founders, data analysts, and business- and tech-side professionals looking for ways to unlock new forms of value in their company. The authors, who are industry leaders, assemble the puzzle pieces into a comprehensive framework for AI value creation: Michael Proksch is an expert on the subject of AI strategy and value creation. He worked with various Fortune 2000 organisations and focuses on optimising business operations building customised AI solutions, and driving organisational adoption of AI through the creation of value and trust. Nisha Paliwal is a senior technology executive. She is known for her expertise in various technology services, focusing on the importance of bringing AI technology, computing resources, data, and talent together in a synchronous and organic way. Wilhelm Bielert is a seasoned senior executive with an extensive of experience in digital transformation, program and project management, and corporate restructuring. With a proven track record, he has successfully led transformative initiatives in multinational corporations, specialising in harnessing the power of AI and other cutting-edge technologies to drive substantial value creation.

This book analyses various models of value creation in projects and businesses by applying different forms of Artificial Intelligence in their products and services. First presenting the main concepts and ideas behind AI, Wodecki assesses different models of technology-based value creation based upon the analysis of over 400 case studies. This framework shows how AI may influence both value creation and competitive advantage (efficiency, creativity and flexibility) within a modern organization. Finally, a conceptual model is formulated to evaluate AI-supported in-company projects and new ventures and identify the key managerial and technical competencies required.

This book includes 15 works by scientists of the Eurasian region, which reveal the various stages of the life cycle of digital transformation The creation of value propositions and their distribution chains is important for the sustainable development of society. This view of sustainable value chains on the part of public administration and business, considering modern scientific research, reveals the problems of education and science in the formation of chains sustainability and their infrastructure. Modern views on the actual problems of the digital service in the creation of value propositions with the participation of development institutions, new educational technologies, and state regulation both at the level of the world community and at the level of individual countries are revealed. The problems of digital transformation of economic actors and industries at different stages of the chain of value creation from a position of sustainable development, innovation in the infrastructure of public administration markets are considered. This book is useful to the academic community and a new generation of infrastructure creators to identify vectors to support the innovative development of value chains.

Autonomous systems are on the frontiers of Artificial Intelligence (AI) research, and they are slowly finding their business applications. Driven mostly by Reinforcement Learning (RL) methods (one of the most difficult, but also the most promising modern AI algorithms), autonomous systems help create self-learning and self-optimising systems, ranging from simple game-playing agents to robots able to efficiently act in completely new environments. Based on in-depth study of more than 100 projects, Andrzej Wodecki explores RL as a key component of modern digital technologies, its real-life applications to activities in a value chain and the ways in which it impacts different industries.