Leong Chan - Applied Artificial Intelligence in Business: Concepts and Cases

Technology is not just limited to technology companies. Managing innovation and technology is no longer a luxury and needs to be understood by all sectors around the world and by both technical and non-technical managers. This book series explores existing and emerging technologies that address current challenges within innovation and technology managements. Each title is developed to provide a set of frameworks, tools and methods that can be adopted by researchers, managers and student in engineering, innovation and technology fields. Research, policy and practice-based books in the series cover topics such as roadmapping, portfolio management, technology forecasting, R&D management, health technologies, bio technologies, transportation management, smart cities, and open innovation, among many others

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When we think about the future of artificial intelligence and machine learning, movies such as The Terminator or iRobot usually come to mind, in which robots grow smarter than humans and begin to take over the world. AI technologies, which are embedded in various business software applications, can make its own judgments based on real-world scenarios, interpret human language, and see, hear, and react to other senses. AI and machine learning are considered as one of the most important applications companies can implement within their business to advance their products and build their technological edge. Whether a startup company or a long-standing firm, many corporations have already started to implement AI into the operations of their business. The ones that have implemented this emerging technology are already starting to see the results and achieve an increase in the speed or efficiency of their operations.

This book explores the concepts and cases of artificial intelligence applications in three interconnected parts. Part I consists of Chaps.. The chapters will explore AI tools in various industrial sectors.

Part I introduces the concepts and theories of artificial intelligence specifically for business applications. We are going to explore the relationship between big data and artificial intelligence, and focus on how they will be used in the business. We will also introduce the business intelligence concept, and different kinds of AI technologies, especially on how they are used in the business world. One of the most important subfields of AI is machine learning, and we are going to introduce basic ideas for most commonly used machine learning techniques so that readers without technical background can understand.

Part II focuses on how AI applications can improve business processes in the key business departments. The most popular area for AI in business is definitely marketing and sales. We will explore related concepts in two sections, Chap..

Part III explores AI applications in various industries. Industries such as energy, healthcare, manufacturing, education, finance, and many others are using artificial intelligence and machine learning nowadays.

Chapter introduces the impact of big data and AI in the insurance industry. It discusses development of insurance technology (insurtech), uses of AI for health and automotive insurance, and enabling technologies of AI (chatbots, NLP, robotic process automation, and others). AI applications in the insurance industry are presented in this chapter as well. We present four case studies: Allstate, Liberty Mutual, State Farm, and Progressive.

Implementations of AI and big data in credit and mortgage are explored in Chap. : AI for credit and mortgage. AI plays a big role in credit and mortgage in areas of fraud detection, risk assessment, loan performance prediction, and customer/borrower experience. Along with discussions of AI technology and application development in this industry, three case studiesUpstart, Affirm, and Monedoare covered in this chapter.

In Chap. , AI for transportation, describes three case studies of AI in Tesla Cars, Uber AI, and AI in WeRide. AI in transportation has been making headlines in autonomous vehicles, powered by neural networks and genetic algorithms.

Real estate has been utilizing AI in inventory management, new sales identification, placement and promotion of house listings, and customer management. Chapter , AI for real estate, discusses those AI application areas and AI-supported real estate platforms as well as explores case studies about Zillow, Redfin, and Compass Real Estate.

In Chap. , AI for education, we present the evolution of AI in education, as well as application of AI in learning platforms. Some highlights include adaptive learning technologies, learning personalization and case studies, Realizeit, Nuance, and Civitas.