Advertisement
AI and Supply Chain Management: Revolutionizing Logistics and Operations
Author: Dr. Anya Sharma, PhD, Professor of Operations Management and AI, MIT Sloan School of Management. Dr. Sharma has over 15 years of experience researching and consulting on the application of artificial intelligence in supply chain optimization.
Publisher: MIT Sloan Management Review, a leading publication known for its insightful analysis of management trends and technological advancements, including the intersection of AI and supply chain management.
Editor: David Lee, Senior Editor, MIT Sloan Management Review, with 20 years of experience editing publications focused on technological innovation and business strategy.
Keywords: AI and supply chain management, artificial intelligence in supply chain, supply chain optimization, AI-powered supply chain, predictive analytics, machine learning supply chain, AI in logistics, supply chain visibility, AI for inventory management, digital supply chain, intelligent automation, supply chain risk management, AI-driven decision making
Abstract: The integration of artificial intelligence (AI) and supply chain management is rapidly transforming the way businesses operate. This article provides a comprehensive overview of how AI is being used to optimize various aspects of the supply chain, from forecasting demand and managing inventory to improving logistics and enhancing risk management. We examine the various AI technologies involved, discuss the challenges of implementation, and explore the future potential of AI and supply chain management.
1. Introduction: The Rise of AI in Supply Chain Management
The global supply chain is a complex network of interconnected activities, encompassing everything from sourcing raw materials to delivering finished goods to consumers. Traditional supply chain management relies heavily on historical data and human expertise, but these approaches often struggle to keep pace with the dynamic and unpredictable nature of modern markets. This is where AI and supply chain management converge. AI, with its ability to analyze vast datasets, identify patterns, and make predictions, is revolutionizing the sector, offering unparalleled opportunities for efficiency, resilience, and profitability. The convergence of AI and supply chain management promises a more agile, responsive, and intelligent supply chain ecosystem.
2. AI Technologies Transforming Supply Chain Management
Several AI technologies are transforming how we approach AI and supply chain management:
Predictive Analytics: Utilizing machine learning algorithms to forecast demand, predict potential disruptions, and optimize inventory levels. AI and supply chain management applications of predictive analytics significantly reduce stockouts and overstocking, leading to cost savings and improved customer satisfaction.
Machine Learning (ML): ML algorithms learn from data to improve their performance over time, enabling more accurate forecasting, better route optimization, and more effective anomaly detection in supply chain processes. The use of ML in AI and supply chain management is essential for continuous improvement and adaptation.
Deep Learning (DL): A subset of ML, DL utilizes artificial neural networks with multiple layers to analyze complex data, offering advancements in image recognition for quality control and natural language processing for improved communication within the supply chain. The advanced capabilities of DL are crucial for handling the increasing complexity of data in modern AI and supply chain management.
Computer Vision: Analyzing images and videos to automate tasks such as quality inspection, damage detection, and warehouse automation. This technology is rapidly becoming an integral component of AI and supply chain management, improving efficiency and reducing errors.
Natural Language Processing (NLP): Processing and understanding human language to automate tasks such as order processing, customer service, and supplier communication. The application of NLP enhances communication and collaboration within AI and supply chain management.
3. Applications of AI in Supply Chain Management
The applications of AI within supply chain management are vast and continually expanding:
Demand Forecasting: AI algorithms analyze historical sales data, market trends, and external factors to provide more accurate demand predictions, reducing forecasting errors and improving inventory management.
Inventory Optimization: AI-powered systems optimize inventory levels by considering factors such as demand forecasts, lead times, and storage costs, minimizing holding costs and preventing stockouts.
Logistics and Transportation: AI optimizes transportation routes, schedules deliveries, and manages fleets more efficiently, reducing transportation costs and improving delivery times.
Supply Chain Risk Management: AI systems identify and assess potential risks, such as supplier disruptions or natural disasters, allowing businesses to proactively mitigate these risks.
Warehouse Management: AI-powered robots and automated systems improve warehouse efficiency, optimize storage space, and accelerate order fulfillment.
Supplier Relationship Management (SRM): AI enhances communication and collaboration with suppliers, leading to improved supplier performance and reduced risk.
Quality Control: AI-powered systems automate quality inspections, identifying defects and ensuring product quality.
4. Challenges and Considerations in Implementing AI in Supply Chain Management
Despite the significant potential benefits, implementing AI in supply chain management presents several challenges:
Data Availability and Quality: AI algorithms require large amounts of high-quality data to function effectively. Many companies lack the necessary data infrastructure or data quality.
Integration with Existing Systems: Integrating AI systems with legacy systems can be complex and costly.
Cost of Implementation: The initial investment in AI technologies and expertise can be substantial.
Lack of Skilled Workforce: A shortage of professionals with the necessary skills to develop, implement, and manage AI systems presents a significant hurdle.
Ethical Considerations: Concerns around data privacy, algorithmic bias, and job displacement need careful consideration.
5. The Future of AI and Supply Chain Management
The future of AI and supply chain management is bright. We can expect to see even more sophisticated applications of AI, including:
Increased Automation: Further automation of tasks across the supply chain, leading to increased efficiency and reduced costs.
Enhanced Visibility and Transparency: Improved visibility into the entire supply chain, enabling better decision-making and risk management.
Greater Resilience: More resilient supply chains that are better able to withstand disruptions.
Sustainable Supply Chains: AI can play a vital role in creating more sustainable supply chains by optimizing resource utilization and reducing waste.
Hyper-Personalization: AI enabling hyper-personalized supply chains, tailoring products and services to individual customer needs.
6. Conclusion
AI and supply chain management are inextricably linked. The integration of AI technologies offers a transformative opportunity to optimize supply chain operations, enhance efficiency, improve decision-making, and build more resilient and sustainable supply chains. While challenges remain, the potential benefits far outweigh the risks, making AI a critical component of future supply chain strategies. Embracing AI and supply chain management is no longer a matter of choice, but a necessity for competitiveness in today's rapidly evolving business landscape.
FAQs
1. What are the main benefits of using AI in supply chain management? Improved forecasting accuracy, optimized inventory levels, reduced transportation costs, enhanced risk management, and increased efficiency.
2. What types of AI technologies are commonly used in supply chain management? Predictive analytics, machine learning, deep learning, computer vision, and natural language processing.
3. What are the biggest challenges in implementing AI in supply chain management? Data availability and quality, integration with existing systems, cost of implementation, and lack of skilled workforce.
4. How can companies overcome the challenges of implementing AI in supply chain management? Investing in data infrastructure, partnering with AI specialists, and developing a skilled workforce.
5. What is the ROI of implementing AI in supply chain management? The ROI varies depending on the specific application and implementation, but significant cost savings and revenue improvements are possible.
6. How does AI improve supply chain visibility? AI provides real-time insights into various aspects of the supply chain, enhancing transparency and enabling proactive decision-making.
7. How can AI help reduce supply chain risks? AI identifies and assesses potential risks, allowing businesses to develop mitigation strategies and improve resilience.
8. What ethical considerations should companies address when using AI in supply chain management? Data privacy, algorithmic bias, and the impact on employment.
9. What is the future of AI and supply chain management? Increased automation, enhanced visibility, greater resilience, sustainable supply chains, and hyper-personalization.
Related Articles:
1. "AI-Powered Demand Forecasting: A Practical Guide": This article provides a step-by-step guide on how to implement AI-powered demand forecasting in your supply chain.
2. "Optimizing Logistics with Machine Learning: Case Studies": This article presents real-world case studies showcasing the successful application of machine learning in logistics optimization.
3. "The Role of Deep Learning in Supply Chain Risk Management": This article explores the use of deep learning algorithms for identifying and mitigating supply chain risks.
4. "Building a Resilient Supply Chain with AI: Strategies and Best Practices": This article provides practical strategies and best practices for building a more resilient supply chain using AI.
5. "AI and the Future of Warehouse Automation": This article discusses the latest advancements in AI-powered warehouse automation and their impact on supply chain efficiency.
6. "Ethical Considerations in AI-Driven Supply Chain Management": This article explores the ethical implications of using AI in supply chain management.
7. "The Impact of AI on Supply Chain Sustainability": This article examines how AI can contribute to building more sustainable supply chains.
8. "Overcoming the Challenges of AI Implementation in Supply Chains": This article provides practical solutions for overcoming the common challenges of implementing AI in supply chains.
9. "Measuring the ROI of AI in Supply Chain Management": This article provides a framework for measuring the return on investment of AI initiatives in supply chain management.
| ai and supply chain management: Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management Dinesh K. Sharma, Madhu Jain, 2022 This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included. The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics. . |
| ai and supply chain management: Artificial Intelligent Techniques for Wireless Communication and Networking R. Kanthavel, K. Anathajothi, S. Balamurugan, R. Karthik Ganesh, 2022-02-24 ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field. Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments. Audience Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies. |
| ai and supply chain management: Blockchain, IoT, and AI Technologies for Supply Chain Management Priyanka Chawla, Adarsh Kumar, Anand Nayyar, Mohd Naved, 2023-05-05 Supply chain management, often known as SCM, refers to the extensive variety of operations that are required to plan, monitor, and coordinate the movement of a product from its raw materials to its finished state in the most time- and money-efficient manner possible. How the supply chain is managed has an impact not only on the quality of the product and the service but also on the distribution, costs, and overall customer experience. Supply chain management is a massive undertaking that needs firms to reevaluate the method in which they operate their supply chains. Blockchain, IoT, and AI Technologies for Supply Chain Management discusses the problems and difficulties that the facilitators of the supply chain confront, in addition to the possible solutions to such problems and difficulties. This book will be the only one of its kind to address the impact of COVID-19 on supply chain systems involving different stakeholders such as producers, dealers, and manufacturers and will provide a foundation for future research opportunities that will allow for the unrestricted expansion and prosperity of business. It will serve as a foundation for academics, scientists, and educationists interested in the use of modern technologies in the field of supply chain management, such as the Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain. In addition to those engaged in research, undergraduate and postgraduate students in higher education can also use this publication as a reference book. This book also presents a multifaceted perspective for the general public, including topics such as computer science, the food business, hotel management, fashion, medical, inventory management, and agricultural spheres. |
| ai and supply chain management: The Oxford Handbook of Supply Chain Management Thomas Y. Choi, Julie Juan Li, Dale S. Rogers, Tobias Schoenherr, Stephan M. Wagner, This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. |
| ai and supply chain management: Utilization of AI Technology in Supply Chain Management Pandey, Digvijay, Pandey, Binay Kumar, Kanike, Uday Kumar, George, A. Shaji, Kaur, Prabjot, 2024-03-01 The surge in digital transformation and the integration of innovative technologies into manufacturing processes have given rise to a pressing issue in supply chain management. Businesses are in dire need of solutions to navigate this complexity and harness the true potential of intelligent supply chains. Utilization of AI Technology in Supply Chain Management is a comprehensive guide tailored for academic scholars seeking to unravel the mysteries of artificial intelligence (AI) and machine learning (ML) in the context of supply chain management. Amid the hype surrounding AI and ML, there exists a critical need to bridge the gap between human expertise and technological advancements. Utilization of AI Technology in Supply Chain Management addresses this necessity by delving into real-world instances where teams have successfully employed these innovative technologies to enhance supply chain performance, reduce inventory, and optimize routes. The adoption of AI and ML is not just a trend; it is the cornerstone of digital acceleration initiatives, making it imperative for scholars to understand and leverage these technologies effectively. |
| ai and supply chain management: AI and Machine Learning Impacts in Intelligent Supply Chain Pandey, Binay Kumar, Kanike, Uday Kumar, George, A. Shaji, Pandey, Digvijay, 2024-01-29 Businesses are facing an unprecedented challenge - the urgent need to adapt and thrive in a world where intelligent factories and supply chains are the new norm. The digital transformation of supply chains is essential for staying competitive, but it is a complex journey fraught with uncertainties. How can organizations harness the power of emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to increase profitability, cut supply chain costs, elevate customer service, and optimize their networks? The answers to these questions are crucial for business survival and success. AI and Machine Learning Impacts in Intelligent Supply Chain is a groundbreaking book that offers a comprehensive solution to the challenges posed by the Industry 4.0 revolution. This book is your indispensable guide to navigating the intricate world of supply chain digital transformation using innovative technologies. It provides real-world examples and insights that illustrate how AI and ML are the keys to solving complex supply chain problems, from inventory management to route optimization and beyond. Whether you are an academic scholar seeking to delve into the impact of AI and ML on supply chain management or a business leader striving to gain a competitive edge, this book is tailored to meet your needs. |
| ai and supply chain management: Artificial Intelligence in Supply Chain Management Calvin Klein, 2023-10-06 |
| ai and supply chain management: Blockchain, IoT, and AI Technologies for Supply Chain Management Veena Grover, |
| ai and supply chain management: Guide to Supply Chain Management David Steven Jacoby, The Economist, 2014-02-25 Globalization, technology and an increasingly competitive business environment have encouraged huge changes in what is known as supply chain management, the art of sourcing components and delivering finished goods to the customer as cost effectively and efficiently as possible. Dell transformed the way people bought and were able to customize computers. Wal-Mart and Tesco have used their huge buying power and logistical skills to ensure the supply and stock management of their stores is finely honed. Manufacturers now make sure that components are where they are needed on the production line just in time for when they are needed and no longer. Such finessing of the way the supply chain works boosts the corporate bottom line and can make the difference between being a market leader or an also ran. This guide explores all the different aspects of supply chain management and gives hundreds of real life examples of what firms have achieved in the field. |
| ai and supply chain management: Data-Driven Technologies and Artificial Intelligence in Supply Chain Mahesh Chand, Vineet Jain, Puneeta Ajmera, 2023-11-22 This book highlights the importance of data-driven technologies and artificial intelligence in supply chain management. It covers important concepts such as enabling technologies in Industry 4.0, the impact of artificial intelligence, and data-driven technologies in lean manufacturing. Provides solutions to solve complex supply chain management issues using artificial intelligence and data-driven technologies. Emphasizes the impact of a data-driven supply chain on quality management. Discusses applications of artificial intelligence, and data-driven technologies in the service industry, and lean manufacturing. Highlights the barriers to implementing artificial intelligence in small and medium enterprises. Presents a better understanding of different risks such as procurement risks, process risks, demand risks, transportation risks, and operational risks. The book comprehensively discusses the applications of artificial intelligence and data-driven technologies in supply chain management for diverse fields such as service industries, manufacturing industries, and healthcare. It further covers the impact of artificial intelligence and data-driven technologies in managing the FMGC supply chain. It will be a valuable resource for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, industrial engineering, manufacturing engineering, production engineering, and computer engineering. |
| ai and supply chain management: Logistics and Supply Chain Management with Artificial Intelligence Techniques , 2004 |
| ai and supply chain management: Blockchain, IoT, and AI Technologies for Supply Chain Management Veena Grover, Balamurugan Balusamy, Mariofanna Milanov, A. Yovan Felix, 2024-07-18 Examine the synergistic possibilities of combining blockchain, IoT, and AI technologies in supply chain management. This book will address the difficulties and possibilities of integrating these technologies and offer helpful implementation advice. The current state of supply chain management involves several challenges, including lack of transparency, limited visibility into product movements, inefficient inventory management, and difficulty in tracking and tracing products. Blockchain, IoT, and AI can potentially address some of these challenges and improve supply chain management. To help illustrate this, case studies and actual instances of businesses implementing or experimenting with blockchain, IoT, and AI technology in their supply chains are included in the book. You’ll review helpful advice on implementation and highlight successful deployments, lessons learned, and the impact of these technologies on supply chain visibility, agility, sustainability, and customer experience. This book further elaborates the fundamental concepts of AI and ML algorithms and demonstrates how AI can process enormous volumes of supply chain data to produce actionable insights, improve inventory control, forecast demand, and increase forecasting precision. This collective work will serve as a comprehensive guide for supply chain professionals, researchers, and technology enthusiasts interested in understanding the potential of blockchain, IoT, and AI technologies in revolutionizing supply chain management practices. What You Will Learn Discuss the evolving landscape of technology, potential advancements, and how Blockchain, IoT, and AI can shape the future of supply chains Gain Insight into upcoming developments and prepare for changing dynamics of the industry Understand intricate details of blockchain, IoT, and AI Technologies in real-life scenarios Who Is This Book For Industry Professionals working in the domain of supply chain management who would be interested in understanding how these technologies can enhance efficiency, transparency, and optimization in their supply chains. |
| ai and supply chain management: Handbook of Research on Applied AI for International Business and Marketing Applications Christiansen, Bryan, Škrinjari?, Tihana, 2020-09-25 Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students. |
| ai and supply chain management: The Art of Structuring Katrin Bergener, Michael Räckers, Armin Stein, 2019-01-25 Structuring, or, as it is referred to in the title of this book, the art of structuring, is one of the core elements in the discipline of Information Systems. While the world is becoming increasingly complex, and a growing number of disciplines are evolving to help make it a better place, structure is what is needed in order to understand and combine the various perspectives and approaches involved. Structure is the essential component that allows us to bridge the gaps between these different worlds, and offers a medium for communication and exchange. The contributions in this book build these bridges, which are vital in order to communicate between different worlds of thought and methodology – be it between Information Systems (IS) research and practice, or between IS research and other research disciplines. They describe how structuring can be and should be done so as to foster communication and collaboration. The topics covered reflect various layers of structure that can serve as bridges: models, processes, data, organizations, and technologies. In turn, these aspects are complemented by visionary outlooks on how structure influences the field. |
| ai and supply chain management: Artificial Intelligence in Industrial Applications Steven Lawrence Fernandes, Tarun K. Sharma, 2021-12-07 This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence. |
| ai and supply chain management: Innovative Supply Chain Management via Digitalization and Artificial Intelligence Kumaresan Perumal, Chiranji Lal Chowdhary, Logan Chella, 2022-04-06 This book focuses on the impact of artificial intelligence (AI) and machine learning (ML) models on supply chain operations in industry 4.0. The chapters illustrate the AI and ML models for all functional areas of operations in SCM. The book also includes examples using ML models like handling supply-to-demand imbalances, triggering automated responses, and reinforcing customer relationships. It describes the evolution of blockchain technology coupled with the ability to automate business logic for the transparency of goods, infrastructure, products, and licenses in software. The book also includes case studies that provide a problem statement and industry overcome by applying ML and AI technologies. This book is suitable for undergraduates, postgraduates, industrial professionals, business executives, entrepreneurs, and freelancers to encourage practical learning on AI and ML algorithms in SCM 4.0. Additionally, this book will provide computer science and information system professionals with the latest technologies embedded in the corporate world. |
| ai and supply chain management: Artificial Intelligence for COVID-19 Diego Oliva, Said Ali Hassan, Ali Mohamed, 2021-07-19 This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations. |
| ai and supply chain management: AI IN ERP AND SUPPLY CHAIN MANAGEMENT Saurabh Suman Choudhuri, 2024-07-01 “AI in ERP and Supply Chain Management” is a comprehensive book that provides an in-depth discussion on the integration of artificial intelligence (AI) in the areas of enterprise resource planning (ERP) and supply chain management (SCM). This book explores the transformational impact of AI on these critical business areas, providing a practical guide to implementing and leveraging AI technologies. The book begins by explaining the basic concepts of AI and its various subfields, such as machine learning, natural language processing, and robotics. It further explains how these AI technologies can be applied to ERP and SCM to increase operational efficiency, optimize decision-making, and unlock new business opportunities. Readers are given valuable information about the potential applications of AI in ERP and SCM, ranging from demand forecasting and inventory management to logistics optimization and supply chain risk management. In addition, the authors discuss the challenges and considerations associated with implementing AI in ERP and SCM, such as data privacy, security, and ethical concerns. They provide guidance on selecting appropriate AI technologies, integrating them with existing systems, and ensuring successful deployment within an organization. The book also explores the future prospects of AI in ERP and SCM, highlighting emerging technologies such as the Internet of Things (IoT), big data analytics, and blockchain and how they can be combined with AI to create even more sophisticated and intelligent systems. “AI in ERP and Supply Chain Management” is a valuable resource for every profession interested in harnessing the power of AI to revolutionize ERP and SCM. With its comprehensive coverage, practical insights, and visionary outlook, this book provides a roadmap for organizations seeking to remain competitive in the era of AI-driven digital transformation. |
| ai and supply chain management: Blockchain and Supply Chain Management Nir Kshetri, 2021-03-03 Blockchain and Supply Chain Management combines discussions of blockchain and supply chains, linking technologies such as artificial intelligence, Internet of Things, satellite imagery, and machine vision. The book examines blockchain's basic concepts, relevant theories, and its roles in meeting key supply chain objectives. The book addresses problems related to inefficiency, opacity, and fraud, helping the digitization process, simplifying the value creation process, and facilitating collaboration. The book is balanced between blockchain and supply chain application and theory, covering the latest technological, organizational and regulatory developments in blockchain from a supply chain perspective. The book discusses the opportunities, barriers, and enablers of blockchain in supply chain policy, along with legal and ethical implications. Supply chain management faces massive disruption with the dynamic changes in global trade, the impact of Covid-19, and technological innovation. Entire industries are also being transformed by blockchain, with some of the most promising applications in supply chain management. - Provides theoretical and practical insights into both blockchain and supply chains - Features numerous illustrative case studies, boxes, tables, and figures - Examines blockchain's impacts on supply chains in four key industries: Food and beverage, healthcare, pharmaceuticals, and finance |
| ai and supply chain management: Revisiting Supply Chain Risk George A. Zsidisin, Michael Henke, 2018-12-18 This book offers a bridge between our current understanding of supply chain risk in practice and theory, and the monumental shifts caused by the emergence of the fourth industrial revolution. Supply chain risk and its management have experienced significant attention in scholarship and practice over the past twenty years. Our understanding of supply chain risk and its many facets, such as uncertainty and vulnerability, has expanded beyond utilizing approaches such as deploying inventory to buffer the initial effects of disruptions. Even with our increased knowledge of supply chain risk, being in the era of lean supply chain practices, digitally managed global supply chains, and closely interconnected networks, firms are exposed as ever to supply chain uncertainties that can damage, or even destroy, their ability to compete in the marketplace. The book acknowledges the criticality of big data analytics in Supply Chain Risk Management (SCRM) processes and provides appropriate tools and approaches for creating robust SCRM processes. Revisiting Supply Chain Risk presents a state-of-the-art look at SCRM through current research and philosophical thought. It is divided into six sections that highlight established themes, as well as provide new insights to developing areas of inquiry and contexts on the topic. Section 1 examines the first step in managing supply chain risk, risk assessment. The chapters in Section 2 encompass resiliency in supply chains, while Section 3 looks at relational and behavioral perspectives from varying units of analysis including consortiums, teams and decision makers. Section 4 focuses on examining supply chain risk in the contexts of sustainability and innovation. Section 5 provides insight on emerging typologies and taxonomies for classifying supply chain risk. The book concludes with Section 6, featuring illustrative case studies as real-world examples in assessing and managing supply chain risk. |
| ai and supply chain management: AI and Machine Learning Applications in Supply Chains and Marketing Masengu, Reason, Tsikada, Charles, Garwi, Jabulani, 2024-10-18 While artificial intelligence (AI) simulates human intelligence in machines, machine learning (ML) enables systems to learn from data without explicit programming. In marketing and supply chain management, AI and ML empower businesses to analyze consumer behavior, personalize experiences, optimize advertising strategies, forecast consumer demands, manage inventory, plan routes, and mitigate risks. Businesses can enhance efficiency, accuracy, decision-making, customer engagement, and cost-effectiveness when integrating AI and ML in marketing and supply chain operations. Further research is necessary to drive success in the dynamic marketplace. AI and Machine Learning Applications in Supply Chains and Marketing bridges the gap between theoretical knowledge and practical application of AI and ML in marketing and supply chain management. It examines emerging technologies that can revolutionize industries by transforming business operations. This book covers topics such as data analysis, sustainable development, and blockchain, and is a useful resource for business owners, economists, marketing professionals, engineers, computer scientists, academicians, and researchers. |
| ai and supply chain management: The Digital Supply Chain Bart L. MacCarthy, Dmitry Ivanov, 2022-06-09 The Digital Supply Chain is a thorough investigation of the underpinning technologies, systems, platforms and models that enable the design, management, and control of digitally connected supply chains. The book examines the origin, emergence and building blocks of the Digital Supply Chain, showing how and where the virtual and physical supply chain worlds interact. It reviews the enabling technologies that underpin digitally controlled supply chains and examines how the discipline of supply chain management is affected by enhanced digital connectivity, discussing purchasing and procurement, supply chain traceability, performance management, and supply chain cyber security. The book provides a rich set of cases on current digital practices and challenges across a range of industrial and business sectors including the retail, textiles and clothing, the automotive industry, food, shipping and international logistics, and SMEs. It concludes with research frontiers, discussing network science for supply chain analysis, challenges in Blockchain applications and in digital supply chain surveillance, as well as the need to re-conceptualize supply chain strategies for digitally transformed supply chains. |
| ai and supply chain management: Responsible AI and Analytics for an Ethical and Inclusive Digitized Society Denis Dennehy, Anastasia Griva, Nancy Pouloudi, Yogesh K. Dwivedi, Ilias Pappas, Matti Mäntymäki, 2021-08-25 This volume constitutes the proceedings of the 20th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2021, held in Galway, Ireland, in September 2021.* The total of 57 full and 8 short papers presented in these volumes were carefully reviewed and selected from 141 submissions. The papers are organized in the following topical sections: AI for Digital Transformation and Public Good; AI & Analytics Decision Making; AI Philosophy, Ethics & Governance; Privacy & Transparency in a Digitized Society; Digital Enabled Sustainable Organizations and Societies; Digital Technologies and Organizational Capabilities; Digitized Supply Chains; Customer Behavior and E-business; Blockchain; Information Systems Development; Social Media & Analytics; and Teaching & Learning. *The conference was held virtually due to the COVID-19 pandemic. |
| ai and supply chain management: Handbook of Research on Innovative Management Using AI in Industry 5.0 Garg, Vikas, Goel, Richa, 2021-11-19 There is no industry left where artificial intelligence is not used in some capacity. The application of this technology has already stretched across a multitude of domains including law and policy; it will soon permeate areas beyond anyone’s imagination. Technology giants such as Google, Apple, and Facebook are already investing their money, effort, and time toward integrating artificial intelligence. As this technology continues to develop and expand, it is critical for everyone to understand the various applications of artificial intelligence and its full potential. The Handbook of Research on Innovative Management Using AI in Industry 5.0 uncovers new and innovative features of artificial intelligence and how it can help in raising economic efficiency at both micro and macro levels and provides a deeper understanding of the relevant aspects of artificial intelligence impacting efficacy for better output. Covering topics such as consumer behavior, information technology, and personalized banking, it is an ideal resource for researchers, academicians, policymakers, business professionals, companies, and students. |
| ai and supply chain management: Technology in Supply Chain Management and Logistics Anthony M. Pagano, Matthew Liotine, 2019-09-07 Technology in Supply Chain Management and Logistics: Current Practice and Future Applications analyzes the implications of these technologies in a variety of supply chain settings, including block chain, Internet of Things (IoT), inventory optimization, and medical supply chain. This book outlines how technologies are being utilized for product planning, materials management and inventory, transportation and distribution, workflow, maintenance, the environment, and in health and safety. Readers will gain a better understanding of the implications of these technologies with respect to value creation, operational effectiveness, investment level, technical migration and general industry acceptance. In addition, the book features case studies, providing a real-world look at supply chain technology implementations, their necessary training requirements, and how these new technologies integrate with existing business technologies. - Identifies emerging supply chain technologies and trends in technology acceptance and utilization levels across various industry sectors - Assists professionals with technology investment decisions, procurement, best values, and how they can be utilized for logistics operations - Features videos showing technology application, including optimization software, cloud computing, mobility, 3D printing, autonomous vehicles, drones and machine learning |
| ai and supply chain management: Applications of Machine Learning Prashant Johri, Jitendra Kumar Verma, Sudip Paul, 2020-05-04 This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics. |
| ai and supply chain management: Logistics 4.0 Turan Paksoy, Cigdem Gonul Kochan, Sadia Samar Ali, 2020-12-17 Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world. |
| ai and supply chain management: The Quantitative Supply Chain Joannès Vermorel, 2018-01-26 The Quantitative Supply Chain represents a novel and disruptive perspective on the optimization of supply chains. It can be seen as a refoundation of many supply chain practices, in particular regarding inventory forecasting, and has been built to make the most of the latest statistical approaches and vast computing resources that are available nowadays. |
| ai and supply chain management: The AI Economy Roger Bootle, 2019-11-26 Gold winner in Business Technology category, 2020 Axiom Business Book Awards Extraordinary innovations in technology promise to transform the world, but how realistic is the claim that AI will change our lives? In this much needed book the acclaimed economist Roger Bootle responds to the fascinating economic questions posed by the age of the robot, steering a path away from tech jargon and alarmism towards a rational explanation of the ways in which the AI revolution will affect us all. Tackling the implications of Artificial Intelligence on growth, productivity, inflation and the distribution of wealth and power, THE AI ECONOMY also examines coming changes to the the way we educate, work and spend our leisure time. A fundamentally optimistic view which will help you plan for changing times, this book explains AI and leads you towards a more certain future. Extraordinary innovations in technology promise to transform the world, but how realistic is the claim that AI will change our lives? In this much needed book the acclaimed economist Roger Bootle responds to the fascinating economic questions posed by the age of the robot, steering a path away from tech jargon and alarmism towards a rational explanation of the ways in which the AI revolution will affect us all. Tackling the implications of Artificial Intelligence on growth, productivity, inflation and the distribution of wealth and power, THE AI ECONOMY also examines coming changes to the the way we educate, work and spend our leisure time. A fundamentally optimistic view which will help you plan for changing times, this book explains AI and leads you towards a more certain future. |
| ai and supply chain management: The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success Allam Hamdan, Aboul Ella Hassanien, Anjum Razzaque, Bahaaeddin Alareeni, 2021-04-11 This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy. |
| ai and supply chain management: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| ai and supply chain management: ADKAR Jeff Hiatt, 2006 In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change. |
| ai and supply chain management: Intelligent Decision Making: An AI-Based Approach Gloria Phillips-Wren, Nikhil Ichalkaranje, 2008-03-04 Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support. |
| ai and supply chain management: Data Science for Supply Chain Forecasting Nicolas Vandeput, 2021-03-22 Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting. This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical traditional models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves. This hands-on book, covering the entire range of forecasting—from the basics all the way to leading-edge models—will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting. |
| ai and supply chain management: Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation Sujeet K. Sharma, Yogesh K. Dwivedi, Bhimaraya Metri, Nripendra P. Rana, 2020-12-15 This two-volume set of IFIP AICT 617 and 618 constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation on Transfer and Diffusion of IT, TDIT 2020, held in Tiruchirappalli, India, in December 2020. The 86 revised full papers and 36 short papers presented were carefully reviewed and selected from 224 submissions. The papers focus on the re-imagination of diffusion and adoption of emerging technologies. They are organized in the following parts: Part I: artificial intelligence and autonomous systems; big data and analytics; blockchain; diffusion and adoption technology; emerging technologies in e-Governance; emerging technologies in consumer decision making and choice; fin-tech applications; healthcare information technology; and Internet of Things Part II: information technology and disaster management; adoption of mobile and platform-based applications; smart cities and digital government; social media; and diffusion of information technology and systems |
| ai and supply chain management: The AI-Powered Enterprise Seth Earley, 2020-04-28 Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence--AI--is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave--rather than be crushed by it--need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development. |
| ai and supply chain management: Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems Alexandre Dolgui, Alain Bernard, David Lemoine, Gregor von Cieminski, David Romero, 2021-08-31 The five-volume set IFIP AICT 630, 631, 632, 633, and 634 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2021, held in Nantes, France, in September 2021.* The 378 papers presented were carefully reviewed and selected from 529 submissions. They discuss artificial intelligence techniques, decision aid and new and renewed paradigms for sustainable and resilient production systems at four-wall factory and value chain levels. The papers are organized in the following topical sections: Part I: artificial intelligence based optimization techniques for demand-driven manufacturing; hybrid approaches for production planning and scheduling; intelligent systems for manufacturing planning and control in the industry 4.0; learning and robust decision support systems for agile manufacturing environments; low-code and model-driven engineering for production system; meta-heuristics and optimization techniques for energy-oriented manufacturing systems; metaheuristics for production systems; modern analytics and new AI-based smart techniques for replenishment and production planning under uncertainty; system identification for manufacturing control applications; and the future of lean thinking and practice Part II: digital transformation of SME manufacturers: the crucial role of standard; digital transformations towards supply chain resiliency; engineering of smart-product-service-systems of the future; lean and Six Sigma in services healthcare; new trends and challenges in reconfigurable, flexible or agile production system; production management in food supply chains; and sustainability in production planning and lot-sizing Part III: autonomous robots in delivery logistics; digital transformation approaches in production management; finance-driven supply chain; gastronomic service system design; modern scheduling and applications in industry 4.0; recent advances in sustainable manufacturing; regular session: green production and circularity concepts; regular session: improvement models and methods for green and innovative systems; regular session: supply chain and routing management; regular session: robotics and human aspects; regular session: classification and data management methods; smart supply chain and production in society 5.0 era; and supply chain risk management under coronavirus Part IV: AI for resilience in global supply chain networks in the context of pandemic disruptions; blockchain in the operations and supply chain management; data-based services as key enablers for smart products, manufacturing and assembly; data-driven methods for supply chain optimization; digital twins based on systems engineering and semantic modeling; digital twins in companies first developments and future challenges; human-centered artificial intelligence in smart manufacturing for the operator 4.0; operations management in engineer-to-order manufacturing; product and asset life cycle management for smart and sustainable manufacturing systems; robotics technologies for control, smart manufacturing and logistics; serious games analytics: improving games and learning support; smart and sustainable production and supply chains; smart methods and techniques for sustainable supply chain management; the new digital lean manufacturing paradigm; and the role of emerging technologies in disaster relief operations: lessons from COVID-19 Part V: data-driven platforms and applications in production and logistics: digital twins and AI for sustainability; regular session: new approaches for routing problem solving; regular session: improvement of design and operation of manufacturing systems; regular session: crossdock and transportation issues; regular session: maintenance improvement and lifecycle management; regular session: additive manufacturing and mass customization; regular session: frameworks and conceptual modelling for systems and services efficiency; regular session: optimization of production and transportation systems; regular session: optimization of supply chain agility and reconfigurability; regular session: advanced modelling approaches; regular session: simulation and optimization of systems performances; regular session: AI-based approaches for quality and performance improvement of production systems; and regular session: risk and performance management of supply chains *The conference was held online. |
| ai and supply chain management: The Digital Supply Chain Challenge Ralf W Seifert, Richard Markoff, 2020-10-05 The Digital Supply Chain Challenge is a distillation of the authors' 50+ years of combined supply chain experience. Their insights and observations - captured in short articles and best-practice case studies - are brought together in one place for supply chain executives to consult at different times during their SCD voyage. |
| ai and supply chain management: Digital Supply Networks: Transform Your Supply Chain and Gain Competitive Advantage with Disruptive Technology and Reimagined Processes Amit Sinha, Ednilson Bernardes, Rafael Calderon, Thorsten Wuest, 2020-07-21 Deliver unprecedented customer value and seize your competitive edge with a transformative digital supply network Digital tech has disrupted life and business as we know it, and supply chain management is no exception. But how exactly does digital transformation affect your business? What are the breakthrough technologies and their capabilities you need to know about? How will digital transformation impact skills requirements and work in general? Do you need to completely revamp your understanding of supply chain management? And most importantly: How do you get started? Digital Supply Networks provides clear answers to these and many other questions. Written by an experienced team comprised of Deloitte consultants and leading problem-driven scholars from a premier research university, this expert guide leads you through the process of improving operations building supply networks, increasing revenue, reimagining business models, and providing added value to customers, stakeholders, and society. You’ll learn everything you need to know about: Stages of development, roles, capabilities, and the benefits of DSN Big data analytics including its attributes, security, and authority Machine learning, Artificial Intelligence, Blockchain, robotics, and the Internet of Things Synchronized planning, intelligent supply, and digital product development Vision, attributes, technology, and benefits of smart manufacturing, dynamic logistics, and fulfillment A playbook to guide the digital transformation journey Drawing from real world-experience and problem-driven academic research, the authors provide an in-depth account of the transformation to digitally connected supply networks. They discuss the limitations of traditional supply chains and the underlying capabilities and potential of digitally-enabled supply flows. The chapters burst with expert insights and real-life use cases grounded in tomorrow’s industry needs. Success in today’s hyper-competitive, fast-paced business landscape, characterized by the risk of black swan events, such as the 2020 COVID-19 global pandemic, requires the reimagination and the digitalization of complex demand-supply systems, more collaborative and connected processes, and smarter, more dynamic data-driven decision making―which can only be achieved through a fully integrated Digital Supply Network. |
| ai and supply chain management: Applications of Artificial Intelligence and Machine Learning Ankur Choudhary, Arun Prakash Agrawal, Rajasvaran Logeswaran, Bhuvan Unhelkar, 2021-07-27 The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications. |
OpenAI
May 21, 2025 · ChatGPT for business just got better—with connectors to internal tools, MCP support, record mode & SSO to Team, and flexible pricing for Enterprise. We believe our …
What is AI - DeepAI
What is AI, and how does it enable machines to perform tasks requiring human intelligence, like speech recognition and decision-making? AI learns and adapts through new data, integrating …
Artificial intelligence - Wikipedia
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, …
ISO - What is artificial intelligence (AI)?
AI spans a wide spectrum of capabilities, but essentially, it falls into two broad categories: weak AI and strong AI. Weak AI, often referred to as artificial narrow intelligence (ANI) or narrow AI, …
Artificial intelligence (AI) | Definition, Examples, Types ...
4 days ago · Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of …
Google AI - How we're making AI helpful for everyone
Discover how Google AI is committed to enriching knowledge, solving complex challenges and helping people grow by building useful AI tools and technologies.
What Is Artificial Intelligence? Definition, Uses, and Types
May 23, 2025 · Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing …
What is artificial intelligence (AI)? - IBM
Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision-making, creativity and autonomy.
What is Artificial Intelligence (AI)? - GeeksforGeeks
Apr 22, 2025 · Narrow AI (Weak AI): This type of AI is designed to perform a specific task or a narrow set of tasks, such as voice assistants or recommendation systems. It excels in one …
Machine learning and generative AI: What are they good for in ...
Jun 2, 2025 · What is generative AI? Generative AI is a newer type of machine learning that can create new content — including text, images, or videos — based on large datasets. Large …
OpenAI
May 21, 2025 · ChatGPT for business just got better—with connectors to internal tools, MCP support, record mode & SSO to Team, and flexible pricing for Enterprise. We believe our …
What is AI - DeepAI
What is AI, and how does it enable machines to perform tasks requiring human intelligence, like speech recognition and decision-making? AI learns and adapts through new data, integrating …
Artificial intelligence - Wikipedia
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, …
ISO - What is artificial intelligence (AI)?
AI spans a wide spectrum of capabilities, but essentially, it falls into two broad categories: weak AI and strong AI. Weak AI, often referred to as artificial narrow intelligence (ANI) or narrow AI, …
Artificial intelligence (AI) | Definition, Examples, Types ...
4 days ago · Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of …
Google AI - How we're making AI helpful for everyone
Discover how Google AI is committed to enriching knowledge, solving complex challenges and helping people grow by building useful AI tools and technologies.
What Is Artificial Intelligence? Definition, Uses, and Types
May 23, 2025 · Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing …
What is artificial intelligence (AI)? - IBM
Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision-making, creativity and autonomy.
What is Artificial Intelligence (AI)? - GeeksforGeeks
Apr 22, 2025 · Narrow AI (Weak AI): This type of AI is designed to perform a specific task or a narrow set of tasks, such as voice assistants or recommendation systems. It excels in one …
Machine learning and generative AI: What are they good for in ...
Jun 2, 2025 · What is generative AI? Generative AI is a newer type of machine learning that can create new content — including text, images, or videos — based on large datasets. Large …
