Artificial Intelligence for Business Optimization: Research and Applications

This is primarily a business book that discusses the research and associated practical application of artificial intelligence (AI) and machine learning (ML) in order to achieve business optimization (BO). AI comprises a wide range of technologies, databases, algorithms, and devices. This book aims for a holistic approach to AI by focusing on developing business strategies that will not only automate but also optimize business functions, processes, and people's behaviors.

Artificial Intelligence for Business Optimization: Research and Applications explores AI and ML from a business viewpoint with the key purpose of enhancing customer value. It applies research methods and fundamentals from a practitioner's viewpoint and incorporates discussions around risks and changes associated with the utilization of AI in business. Furthermore, governance risks, privacy, and security are also addressed in this book to ensure compliance with AI/ML applications. Readers should find direct and practical applications of the discussions in this book quite useful in their work environment. Researchers will find many ideas to further explore the applications of AI to business.

Dr Bhuvan Unhelkar (BE, MDBA, MSc, PhD, FACS) has extensive strategic and hands- on professional experience in the Information and Communication Technologies (ICT) industry. He is a full Professor and lead faculty of IT at the University of South Florida Sarasota-Manatee (USFSM), and is the founder and Consultant at MethodScience and PlatiFi. He is also an adjunct Professor at Western Sydney University, Australia and an honorary Professor at Amity University, India . His current industrial research interests include AI and ML in Business Optimization, Big Data and business value and Business Analysis in the context of Agile. Dr. Unhelkar holds a Certificate-IV in TAA and TAE, Professional Scrum Master - I, SAFe (Scaled Agile Framework for Enterprise) Leader and is a Certified Business Analysis Professional(R) (CBAP of the IIBA). Tad Gonsalves is full Professor in the Department of Information & Communication Sciences, Sophia University, Tokyo, Japan. Dr. Gonsalves' research areas include Bio-inspired Optimization techniques and application of Deep Learning techniques to diverse problems like autonomous driving, drones, digital art and computational linguistics. He holds a BS in theoretical Physics and MS in Astrophysics and earned his PhD in Information Systems from Sophia University, Tokyo, Japan. His research lab in Tokyo specializes in multi-GPU computing. Dr. Gonsalves is the author of Introduction to AI: A Non-Technical Introduction, (Sophia Univ. Press, 2017) which serves as a standard AI textbook for the university curriculum.