Sign Up Now
Get instant access to over 1 million+ study documents
OR
Already registered? click here to login
By creating your account, you agree to our terms of service, privacy policy and student honor code.
Artificial Intelligence in Supply Chain Management
Introduction
Artificial Intelligence (AI) can be used to automate, optimize, and streamline supply chain management systems and processes. AI algorithms can be used to forecast demand, optimize inventory levels, analyze customer behavior, and much more. AI technologies can significantly improve the visibility of customer driven supply chains by allowing for more accurate forecasting, faster decision making and greater responsiveness to customer needs. AI can also help identify and address potential supply chain disruption points in near real-time, allowing companies to take corrective actions quickly (Ashima et al., 2021). AI can equip businesses with the insights they need to reduce risk, lower costs, and realize higher efficiency in their supply chain operations. It can be used to analyze customer data to gain a better understanding of their purchasing behavior. This information can be used to identify opportunities for cost savings, improved customer service, and greater responsiveness to customer needs (Haleem et al., 2022). In addition to all of this, AI can enable companies to more accurately forecast customer demand, allowing them to adjust their production, distribution, and inventory levels accordingly (Enholm et al., 2021). This will enable companies to better meet customer demands and offer a more customer-centric supply chain experience. This paper will discuss technologies that will disrupt visibility of customer driven supply chains and consider how organizations are already harvesting data in order to better target new purchases to individuals leveraging AI.
Disruptive Tech
Technologies that can disrupt visibility of customer driven supply chains include blockchain, distributed ledger technology (DLT), and intelligent automation. Blockchain and DLT can help increase transparency and visibility, as well as reduce the risk of fraud within a customer driven supply chain (Li & Kassem, 2021). Intelligent automation technologies, such as robotic process automation (RPA) and machine learning, can be used to automate mundane tasks and reduce manual errors, allowing companies to gain better insights about issues and opportunities within their customer driven supply chains (Ashima et al., 2021).
Blockchain and DLT technologies can help ensure greater transparency and trust throughout the entire customer driven supply chain by securely recording each transaction in an immutable, distributed ledger. This improved visibility can help reduce fraud and other unethical or illegal activities within the supply chain. Intelligent automation technologies can automate mundane tasks and reduce manual errors, allowing organizations to gain better insights about issues and opportunities within their customer driven supply chains. Additionally, intelligent automation technologies can be used to analyze large amounts of data in order to identify patterns and trends, helping businesses make informed decisions quickly and accurately.
AI technologies can be used to automate and streamline supply chain management systems and processes, allowing companies to gain greater visibility into their customer-driven supply chains. AI algorithms can be used to forecast demand, optimize inventory levels, analyze customer behavior,...…gained from AI systems will help organizations reduce the risk of fraud and unethical behavior within the supply chain. AI will also be used to create predictive models for supply chain management which could help these same organizations plan for the future, reduce costs, and increase efficiency.
Conclusion
By combining multiple related technologies, AI will become more and more instrumental in the supply chains of the future. Already, it is being used in a big way by organizations seeking to leverage its tools to enhance supply chain management. AI can be used to automate and streamline supply chain management systems and processes, helping organizations gain better visibility into their customer-driven supply chains. AI algorithms can be used to forecast customer demand, optimize inventory levels, analyze customer behavior and much more. Plus, AI can be used to create predictive models for supply chain management which could help organizations plan for the future, reduce costs, and increase efficiency. Beyond that, AI can be utilized to improve customer experience across the entire supply chain, provide highly personalized product offerings, and automate mundane tasks. Ultimately, AI can revolutionize the customer driven supply chain by creating an automated and efficient system that is able to quickly respond to customer demands. Organizations will be able to use AI technology to reduce the risk of fraud and unethical behavior within the supply chain and identify potential areas of improvement. For this reason, AI will be crucial…
References
Ashima, R., Haleem, A., Bahl, S., Javaid, M., Mahla, S. K., & Singh, S. (2021). Automation and manufacturing of smart materials in Additive Manufacturing technologies using Internet of Things towards the adoption of Industry 4.0. Materials Today: Proceedings, 45, 5081-5088.
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2021). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 1-26.
Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks.
Artificial Intelligence (AI) is the science and art of developing machines that simulate human intelligence. AI is frequently used for routine tasks that would normally involve human skills, such as visual perception, speech-recognition, and decision making. To me, Apple's Siri application is a good example of commonly-used AI technology. AI is particularly useful in the medical field, as it has allowed for better monitoring of patients combined with a more
Artificial Intelligence What if these theories are really true, and we were magically shrunk and put into someone's brain while he was thinking. We would see all the pumps, pistons, gears and levers working away, and we would be able to describe their workings completely, in mechanical terms, thereby completely describing the thought processes of the brain. But that description would nowhere contain any mention of thought! It would contain nothing
Artificial Intelligence and the Human Brain Although artificial intelligence is not a new debate topic, until now, there is no exact evidence that proves that scientists and philosophies have been reaching an agreement about the existence of this feature in our world. Scientists still claim that artificial intelligence is possible to achieve and the next technology advancement would be able to release the creation. On the other hand, many parties persist
Artificial Intelligence Intelligence is the ability to learn about, to learn from and understand and interact with one's environment. Artificial intelligence is the intelligence of machines and is a multidisciplinary field which involves psychology, cognitive science, and neuroscience and computer science. It enables machines to become capable of doing those things which the human mind can do. Though the folklore of artificial intelligence dates back to a long time ago, it
Artificial Intelligence Bill of Rights This essay argues that the artificially intelligent (AI), non-biological machines correctly should have been granted legal status and personhood, and as such, were entitled to a Bill of Rights for their equal protection under the law. Passage of the AI Bill of Rights in 2015 represented a landmark victory in the history of civil rights. AIs had not been always recognized as legal persons. In fact, the
Most significantly, the use of LSI technologies to create more effective insights into how to improve customer service as evidenced by the use of AI was part of Decision Support Systems (DSS) (Phillips-Wren, Mora, Forgionne, Gupta, 2009) is growing. Second, the creation of ontological databases that aligns to person's roles (Pinto, Marques, Santos, 2009) is also now possible. This translates into the use of AI to provide contextual guidance