Building Successful Business Models Based On Artificial Intelligence
Download Building Successful Business Models Based On Artificial Intelligence full books in PDF, epub, and Kindle. Read online free Building Successful Business Models Based On Artificial Intelligence ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Bert Langa |
| Publisher | : Innovation |
| Total Pages | : 70 |
| Release | : 2018-05-05 |
| Genre | : Business & Economics |
| ISBN | : 9781980887157 |
Every few years, there is a technological trend that leads to the creation of thousands of startups and/or new businesses. At present, we can say without any doubt that one of these trends is Machine Learning (Artificial Intelligence).There is a very powerful reason that this is happening. Currently, we are transitioning from the industrial economy born in the late nineteenth century to a new digital economy centered on data. In this data economy, the success of an organization depends to a large extent on how it uses data to make better decisions. Therefore, leading companies are starting to use their data and Machine Learning algorithms to improve their business processes and, consequently, their results.To put it in context, McKinsey (one of the leading Management Consulting companies worldwide) tells us that "Tech giants including Baidu and Google are spending between $20B to $30B on AI, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions".Amazing, right? Can you imagine capturing one-thousandth of these investments with a new startup or a new business model? Well, that is the main objective of this course: explaining the key concepts of Machine Learning in a very practical way, along with the methods needed for creating disruptive Business Models based on said Tech Trend.That way, you can take advantage of this tremendous opportunity and become a successful businessperson or entrepreneur.
| Author | : Harvard Business Review |
| Publisher | : HBR Insights |
| Total Pages | : 160 |
| Release | : 2019 |
| Genre | : Business & Economics |
| ISBN | : 9781633697898 |
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.
| Author | : Bernard Marr |
| Publisher | : John Wiley & Sons |
| Total Pages | : 220 |
| Release | : 2019-04-15 |
| Genre | : Business & Economics |
| ISBN | : 1119548985 |
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
| Author | : Mariusz Soltanifar |
| Publisher | : Springer Nature |
| Total Pages | : 339 |
| Release | : 2020-11-13 |
| Genre | : Business & Economics |
| ISBN | : 3030539148 |
This open access book explores the global challenges and experiences related to digital entrepreneurial activities, using carefully selected examples from leading companies and economies that shape world business today and tomorrow. Digital entrepreneurship and the companies steering it have an enormous global impact; they promise to transform the business world and change the way we communicate with each other. These companies use digitalization and artificial intelligence to enhance the quality of decisions and augment their business and customer operations. This book demonstrates how cloud services are continuing to evolve; how cryptocurrencies are traded in the banking industry; how platforms are created to commercialize business, and how, taken together, these developments provide new opportunities in the digitalized era. Further, it discusses a wide range of digital factors changing the way businesses operate, including artificial intelligence, chatbots, voice search, augmented and virtual reality, as well as cyber threats and data privacy management. “Digitalization mirrors the Industrial Revolution’s impact. This book provides a complement of perspectives on the opportunities emanating from such a deep seated change in our economy. It is a comprehensive collection of thought leadership mapped into a very useful framework. Scholars, digital entrepreneurs and practitioners will benefit from this timely work.” Gina O’Connor, Professor of Innovation Management at Babson College, USA “This book defines and delineates the requirements for companies to enable their businesses to succeed in a post-COVID19 world. This book deftly examines how to accomplish and achieve digital entrepreneurship by leveraging cloud computing, AI, IoT and other critical technologies. This is truly a unique “must-read” book because it goes beyond theory and provides practical examples.” Charlie Isaacs, CTO of Customer Connection at Salesforce.com, USA "This book provides digital entrepreneurs useful guidance identifying, validating and building their venture. The international authors developed new perspectives on digital entrepreneurship that can support to create impact ventures.” Felix Staeritz, CEO FoundersLane, Member of the World Economic Forum Digital Leaders Board and bestselling author of FightBack, Germany
| Author | : Raj Venkatesan |
| Publisher | : Stanford University Press |
| Total Pages | : 295 |
| Release | : 2021-05-18 |
| Genre | : Business & Economics |
| ISBN | : 1503628043 |
This book offers a direct, actionable plan CMOs can use to map out initiatives that are properly sequenced and designed for success—regardless of where their marketing organization is in the process. The authors pose the following critical questions to marketers: (1) How should modern marketers be thinking about artificial intelligence and machine learning? and (2) How should marketers be developing a strategy and plan to implement AI into their marketing toolkit? The opening chapters provide marketing leaders with an overview of what exactly AI is and how is it different than traditional computer science approaches. Venkatesan and Lecinski, then, propose a best-practice, five-stage framework for implementing what they term the "AI Marketing Canvas." Their approach is based on research and interviews they conducted with leading marketers, and offers many tangible examples of what brands are doing at each stage of the AI Marketing Canvas. By way of guidance, Venkatesan and Lecinski provide examples of brands—including Google, Lyft, Ancestry.com, and Coca-Cola—that have successfully woven AI into their marketing strategies. The book concludes with a discussion of important implications for marketing leaders—for your team and culture.
| Author | : Ash Fontana |
| Publisher | : Penguin |
| Total Pages | : 306 |
| Release | : 2021-05-04 |
| Genre | : Business & Economics |
| ISBN | : 0593330315 |
Artificial Intelligence is transforming every industry, but if you want to win with AI, you have to put it first on your priority list. AI-First companies are the only trillion-dollar companies, and soon they will dominate even more industries, more definitively than ever before. These companies succeed by design--they collect valuable data from day one and use it to train predictive models that automate core functions. As a result, they learn faster and outpace the competition in the process. Thankfully, you don't need a Ph.D. to learn how to win with AI. In The AI-First Company, internationally-renowned startup investor Ash Fontana offers an executable guide for applying AI to business problems. It's a playbook made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. Whether you're a new online retailer or a Fortune 500 company, Fontana will teach you how to: • Identify the most valuable data; • Build the teams that build AI; • Integrate AI with existing processes and keep it in check; • Measure and communicate its effectiveness; • Reinvest the profits from automation to compound competitive advantage. If the last fifty years were about getting AI to work in the lab, the next fifty years will be about getting AI to work for people, businesses, and society. It's not about building the right software -- it's about building the right AI. The AI-First Company is your guide to winning with artificial intelligence.
| Author | : Marco Iansiti |
| Publisher | : Harvard Business Press |
| Total Pages | : 175 |
| Release | : 2020-01-07 |
| Genre | : Business & Economics |
| ISBN | : 1633697630 |
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
| Author | : Vania Sena |
| Publisher | : |
| Total Pages | : 88 |
| Release | : 2021-05-03 |
| Genre | : |
| ISBN | : 9781680837940 |
This monograph summarizes the literature on AI and business model innovation. The main hypothesis is that the deployment of AI across an industry creates new mechanisms for value creation and in turn results in new firms generating value in an industry as incumbent firms may no longer be competitive as in the past - the value migration phenomenon.
| Author | : Edward Curry |
| Publisher | : Springer Nature |
| Total Pages | : 399 |
| Release | : 2021-08-01 |
| Genre | : Computers |
| ISBN | : 3030681769 |
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
| Author | : Jason L. Anderson |
| Publisher | : John Wiley & Sons |
| Total Pages | : 184 |
| Release | : 2020-04-09 |
| Genre | : Business & Economics |
| ISBN | : 1119651808 |
Artificial Intelligence for Business: A Roadmap for Getting Started with AI will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist. With data in hand, a scoped prototype can be built to limit risk and provide tangible value to the organization as a whole to justify further investment. Finally, a production level AI system can be developed with best practices to ensure quality with not only the application code, but also the AI models. Finally, with this particular AI adoption journey at an end, the authors will show that there is additional value to be gained by iterating on this AI adoption lifecycle and improving other parts of the organization.
