AI and Machine Learning Impacts in Intelligent Supply Chain
Artificial intelligence (AI) and machine learning (ML) are having a huge impact on the business of supply chain management, which is resulting in that industry undergoing a significant transition. This is due to the fact that AI and ML are becoming more advanced. This is a direct consequence of the technologies that are currently available. These technical developments (Berente, N.,et al.(2021)) are currently being put to use in order to raise productivity, improve the efficiency of operations, and make better decisions overall.
The proliferation of artificial intelligence and machine learning is having a wide range of effects on the supply chain (Janvier-James, A.M. (2012)). These changes are occurring for a variety of reasons. Some of these methods are broken down into more specific categories below.
The utilisation of artificial intelligence makes it feasible to carry out an in-depth analysis of historical data (Babu, S. Z. D. et al., 2022), which, in turn, makes it possible to provide more precise forecasts on anticipated levels of demand in the future. By making use of this information, you may help improve inventory (Pandey, B. K., et al. (2021))levels and reduce the likelihood of stockouts occurring.
The use of artificial intelligence (AI) in the optimisation of travel routes for automobiles has the potential to significantly reduce the amount of time spent commuting as well as the quantity of fuel that is consumed.
Administration of the storage facility: It is feasible that one day artificial intelligence (Pandey, B. K., & Pandey, D., 2023) will be able to automate a significant proportion of warehouse activities, such as picking items up and putting them in boxes. It is possible that this will result in decreased costs associated with employment while also boosting the general productivity of the workforce. This would be a win-win situation (Khasis, D. (2019)).
Detecting fraudulent behaviour in regards to financial dealings is one of the many applications of artificial intelligence (AI), such as those involving stolen credit cards and other forms of financial information. This is just one of a number of other uses for AI (Pramanik, S. et al., 2023), which has a lot of other uses as well. This might be helpful in reducing the possibility of a firm incurring monetary losses as a consequence of a risk, which would be beneficial to the company.
With the assistance of artificial intelligence (Gupta, R. et al., 2023), potential threats to a supply chain, such as those brought on by natural disasters or political unrest, might be discovered, and subsequently, these threats could be neutralised with the aid of the aforementioned technology. The application of artificial intelligence makes it feasible to not only recognise but also eliminate the presence of any potential risks (Meslie, Y.,et al. (2021)).
AI (Anand, R. et al., 2023) can be used to provide customised customer care, such as by replying to inquiries regarding purchases or tracking shipments. This can be accomplished in the context of customer service. One way to accomplish this is by keeping track (Pandey, D.,et al.(2021)) of shipments, for instance. Two instances of this would be keeping track of shipments and providing information in answer to questions about orders that have been asked. The fact that tracking information is made available is another piece of evidence that demonstrates the usefulness of this idea.
These are only a few of the ways that artificial intelligence and machine learning are having an effect on the supply chain; there are many more. There are still a great many more. There are still a very significant number left. If we make the reasonable assumption that the development of these technologies will continue, as is the case here, then we can anticipate that they will have an even greater influence on the sector in which they are employed (Liu, C.,et al.(2016)).
The following are some examples of artificial intelligence and machine learning being put to use in the supply chain of today, and they are concrete examples of how these technologies are being utilised:
The use of technology based on artificial intelligence (AI) is assisting Amazon in improving the efficiency of its warehouse operations. The company uses artificial intelligence and robotics to pick and pack the things that customers have requested(Long, D., & Magerko, B. (2020)) and the company also uses artificial intelligence to determine the delivery routes that are the most efficient in terms of both time and money.
Artificial intelligence is currently being utilised by the world's largest retailer, Walmart, in an effort to better anticipate the demand that customers will have for a wide assortment of products. This information is useful to the organisation because it enables them to prevent stockouts and increases the likelihood that they will always have a suitable quantity of goods available (Nishitha, P., & Pandey, D. (2021)).
When it comes to tracking packages, UPS is now employing artificial intelligence technologies, which was not the case in the past. The organisation makes use of both artificial intelligence and sensors in order to keep track of the products' most up-to-date locations in real time and to calculate an estimate of when they will be transported to their final destinations (Pandey, B. K., et al. (2021)).
FedEx is employing artificial intelligence to assist in its fight against fraudulent behaviour. The use of possibly fraudulent transactions, such as those that entail the use of stolen credit cards and other forms of financial information, can be identified as potentially fraudulent by the company through the use of machine learning (Kumar, M. S., et al. (2021).
These are just a few instances of the numerous applications of artificial intelligence and machine learning that are now being researched and put into practice in supply chains. There are, of course, many more. There is a very wide variety of software that can be used. If we make the reasonable assumption that the development of these technologies will continue, as is the case here, then we can anticipate that they will have an even greater influence on the sector in which they are employed (Singh, H., et al. (2022).
In spite of the fact that the use of artificial intelligence and machine learning in the supply chain is still in its infancy, it is abundantly clear that these technologies have the potential to radically revolutionise the industry(Jain, V., Kumar, et al. (2017).). Despite the fact that the supply chain is still in its formative years, this is the case. This is especially true when one considers the dizzyingly quick pace at which the development of these technologies is proceeding. Artificial intelligence and machine learning have the potential to assist businesses in increasing their bottom line by improving the efficiency, precision, and resiliency of supply chains. This is something that can be accomplished through the use of machine learning (Iyyanar, P. et al., 2023) and artificial intelligence. Another advantage for customers is that this might assist companies in providing better customer service to their target demographic.