Artificial Intelligence (AI) and Data Analytics (DA)

Helena S. Wisniewski

Chapter 3 in Global Supply Chains in the Age of AI:Strategies and Emerging Technologies, 2025, pp 45-86 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The following sections are included:IntroductionExplanation of AIAI timeline and evolutionThe recent AI explosionAI, Neural Networks, and Machine Learning — Definitions and TypesNeural NetworksHow our brains workDeep neural networksHow many connections are there in our digit example?Backpropagation teaching the neural network to learnConvolutional neural networks (CNNs)Amazon use case — AI to optimize its supply chainAlibaba cloud AI use caseAI, the COVID-19 Vaccine, and Supply ChainsModerna AI use caseNatural Language Processing (NLP)UPS chatbot use caseErnest & Young use caseBusiness Analytics (BA), Data Analytics (DA), Business Intelligence (BI), and Big Data Analytics (BDA)Business intelligence (BI)Business analytics (BA)Data analytics (DA)In supply chain management (SCM), BI, DA, and BA play a critical roleCase study — United parcel services (UPS)Chapter SummaryBibliography

Keywords: Global Supply Chain Management and Logistics; Emerging Technologies; AI; Neural Networks; Digital Twins; IoT; Data analytics; Robotics; Automated Systems; Autonomous Vehicles; Cyber Security; Augmented Realty; Virtual Reality; Data Analytics; Blockchain; Quantum Computing; Supply Chain Vulnerabilities; Geopolitical Influences on Supply Chains; Reshoring; Nearshoring; COVID Pandemic; Belt and Road Initiative; Ransomware; Non Petra Virus; Bullwhip Effect; Warehouse Management System; Distributed Order Management; Transportation Management; Kanban; Total Quality Management; Six Sigma (search for similar items in EconPapers)
JEL-codes: M1 M11 O33 (search for similar items in EconPapers)
Date: 2025
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