The Effects of Artificial Intelligence on Supply Chain Management

The Effects of Artificial Intelligence on Supply Chain Management

Sanjeet Singh, Geetika Madaan, H. R. Swapna, Lakshmi Lakshmi, Rashmi Darshan Mahajan, A. Shaji George
Copyright: © 2024 |Pages: 19
DOI: 10.4018/979-8-3693-3593-2.ch005
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Abstract

Artificial intelligence (AI) is already processing the flood of operational data coming in from a variety of devices and cloud apps, and it will continue to do so at an unprecedented rate in the near future. Adaptable and learnable goods, processes, and systems are being developed thanks to the use of sophisticated mathematical techniques made possible by this technology. In 2010, the authors foresaw these changes, which they dubbed the “smarter supply chain of the future.” The study predicted the need for more sophisticated supply networks. Instrumented machines, such as sensors, RFID tags, metres, actuators, GPS systems, and more, will progressively produce data that was formerly produced by humans. Stock will automatically be counted. The contents of containers may be detected. Interconnected parts, goods, and other smart things utilised in supply chain monitoring will all be interconnected alongside customers, suppliers, and IT systems.
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Introduction

Artificial intelligence (AI) is already processing the flood of operational data coming in from a variety of electronics devices (Sharma, M. et al., 2022) and cloud apps, and it will continue to do so at an unprecedented rate in the near future. Adaptable and learnable goods, processes, and systems are being developed thanks to the use of sophisticated mathematical techniques (Bessant, Y. A. et al., 2023) made possible by this technology. In 2010, we foresaw these changes, which we dubbed the “smarter supply chain of the future.”. The study predicted the need for more sophisticated supply networks:

  • Instrumented: Machines, such as sensors (Du John, H. V. et al.,2021), RFID tags, metres, actuators, GPS systems, and more, will progressively produce secure data (Pandey, D. et al.,2021) that was formerly produced by humans. Stock will automatically be counted. The contents of containers may be detected. If pallets are misplaced, they will notify the appropriate personnel.

  • Interconnected: Parts, goods, and other smart things utilised in supply chain monitoring will all be interconnected alongside customers, suppliers, and IT systems (Pandey, J. K. et al.,2022). With widespread connection, supply chain networks all around the globe may coordinate their planning and decision-making.

  • Intelligent: In addition, these supply chain choices will be much more astute. Decision makers will be able to use cutting-edge analytics and modelling (Anand, R. et al.,2023) to weigh potential outcomes against an extraordinarily dynamic and interconnected set of risks and restrictions. More sensitive and less dependent on human input, intelligent systems (Revathi, T. K. et al.,2022) will also be able to make judgments independently. Our forecasts are coming true in under a decade.

“Adaptive (Jayapoorani, S. et al.,2023) robots use data from semi-conductor-based electronics devices (Du John, H. V. et al., 2022) and other sources of structured and unstructured information to train themselves and make choices independently. Tools using natural language processing (NLP) can interpret human speech and respond appropriately. Demand responsiveness, inventory and network optimization, preventive maintenance, and digital manufacturing are just some of the areas where predictive analytics are being put to use. To better respond to machine-generated, enhanced intelligence (Singh, H. et al.,2022), supply chains may now benefit from search and pattern recognition algorithms that are not only predictive but also hierarchical, and which examine data (Pandey, B. K. et al.,2023) in real time.”When we speak about supply chain visibility, it does not merely mean insight into your own supply chain,” stated Bob Stoffel, former Senior Vice President, Engineering, Strategy, and Supply Chain at UPS. The increased transparency between partners paves the way for more decentralised, customer-centric decision making.”

Innovation in the supply chain is increasingly dependent on artificial intelligence. In the next three years, over half of supply chain executives plan to spend most heavily in artificial intelligence/cognitive computing, parallel computing (Pandey, B. K. et al.,2011) and cloud applications. To investigate the effect that AI and cognitive computing solutions are having on the supply chain and operations, we polled top-level managers in a variety of sectors and regions. More than 1,600 top-level executives were polled on their objectives and anticipated returns from investing in artificial intelligence (AI) (Iyyanar, P. et al.,2023) and cognitive computing for operations, supply chain, and manufacturing.

Our research, titled “Welcome to the cognitive supply chain,” demonstrates that chief executive officers and chief security officers are vigorously reimagining organisational structures, processes, and systems.They are committed to supporting the CEO in establishing agile business models, collaborating with the CMO to aid in the implementation of the company's go-to-market strategy, and investing in and investigating novel approaches to supply chain optimization. Forward-thinking businesses are integrating AI and cognitive technology into their offerings and processes. Some people have already arrived in the future, while others have just started off.

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