AI and the Supply Chain: What Role Can It Play?

AI is playing an ever-growing role in manufacturing. Start-ups have begun to develop AI solutions for a number of sub-fields within manufacturing. One such area is supply chain management.

Over the past few years, there have been a number of exciting technological developments in supply chain management that rely upon AI. AI’s popularity shows no signs of slowing down, though – read on to learn what we can expect to see in the future.

What Role Does AI Play in Today’s Supply Chain?

Today, AI plays a role in making supply chain management more efficient and effective.

For example, AI can help suppliers predict demand. Machine learning examines data to discover hidden patterns, such as seasonal demands or correlations between demand and weather patterns. With that knowledge, companies can make better operational choices that will boost the bottom line.

Another use case for AI is in helping manage warehouses more effectively. AI for warehouse management also incorporates predictive analytics to determine the likelihood of a customer order. For example, if a clothing manufacturer supplies coats to a particular retailer, and that retailer launched an ad campaign in advance of the winter season, the software would tell the manufacturer that it should increase its supply of coats to meet anticipated demand.

Chatbots also have a role to play in supply chain management. Instead of having to talk to a human being (and wait for an answer about what’s in stock and what’s not), a chatbot can provide that information within moments. That keeps the flow of business going.

What Role Could AI Play in Tomorrow’s Supply Chain?

As AI continues to become more prevalent in the supply chain, we can expect to see more applications of this technology. What’s in store for the future?

Experts predict that the use of natural language processing (NLP) will grow within supply chain management. NLP is a method of communicating with intelligent systems using text or the spoken word. Potentially, NLP could decipher supplier data sets in other languages, reducing barriers between suppliers and customers.

Another possible use for AI in the supply chain is machine learning for the supplier relationship management process. Machine learning refers to a machine’s ability to learn without being explicitly programmed. This technology could come into play when deciding to do business with a supplier. A machine could easily and quickly analyze data sets to make the right decision, while it could take a human days, if not longer.

AI can also be used to plot smarter routes that allow goods to get from point A to point B without being damaged or being late. Delays in shipping cost suppliers financially as well as hurt their reputations, so this will be a boon.

With manufacturers continuously looking for ways to improve supply chain management – AI offers some clear solutions.

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