The Impacts of Technology on Supply Chain Management : AI and Machine Learning
Zhang, Shanshan (2025)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025111428104
https://urn.fi/URN:NBN:fi:amk-2025111428104
Tiivistelmä
Today’s business world is too competitive; it is no longer only about connecting product supply logistics; instead, it is also a responsibility and strategic direction. Behind this change is a revolution in technology that has transformed the methods organizations use to manage their supply chains. Everything from inventory optimization and supplier collaboration to risk management and demand response can be addressed through technology in building an efficient supply chain.
AI and ML represent the most outstanding technological progress in the supply chain, so both academically and practically speaking, it has high relevance. Companies should identify the treasury they are wasting and where migration to other more efficient technologies can invigorate supply chains, thereby achieving innovation, outstanding performance and a special source of overall competitive advantage for themselves.
For this study, key findings are clear: when companies gain real-time visibility into supply chain dynamics, everything changes, in both scope and number, can improve efficiency and raise quality, and reduce costs over the value chain. Predictive risk monitoring and control processes of advanced AI and ML offer resilient supply, a necessary quality for avoiding influence from risk issues, utilizing AI and ML to optimize supply chains, lower production costs, and increase efficiency. It also helps enable new business models, which will not only be more profitable but also less polluting.
AI and ML represent the most outstanding technological progress in the supply chain, so both academically and practically speaking, it has high relevance. Companies should identify the treasury they are wasting and where migration to other more efficient technologies can invigorate supply chains, thereby achieving innovation, outstanding performance and a special source of overall competitive advantage for themselves.
For this study, key findings are clear: when companies gain real-time visibility into supply chain dynamics, everything changes, in both scope and number, can improve efficiency and raise quality, and reduce costs over the value chain. Predictive risk monitoring and control processes of advanced AI and ML offer resilient supply, a necessary quality for avoiding influence from risk issues, utilizing AI and ML to optimize supply chains, lower production costs, and increase efficiency. It also helps enable new business models, which will not only be more profitable but also less polluting.