Managing supply chain challenges with Artificial Intelligence

Supply chains are the backbone of business. The efficiency of the supply chain of a business affects several things from product quality and delivery times to costs of production as well as customer satisfaction. All these things finally affect productivity and profitability. The pandemic has brought the focus sharply to the supply chains and their resiliency.

Now, the supply chain related challenges including sustainability challenges and costs have grown in complexity. While managing unexpected disruptions is critical for maintaining supply chain efficiency, proactively managing these risks has become exceedingly difficult.

What is making it challenging to manage these risks is that a large number of businesses are operating with supply chains built for a different era and that are not ready for the disruptions like those caused by the pandemic. They do not have the capabilities required to better predict and manage disruptions and optimize inventory. The lack of visibility and transparency in supply chain processes makes it difficult to manage risks.

The visibility challenge arises mainly due to the fact that supply chains have to deal with tons of data scattered across several processes, as well as dozens of internal and external sources and siloed systems. It makes it highly complex if not altogether impossible to manage the entire supply chain. The result is unnecessary risks and exposure as well as disruptions, delays and increased costs.


There are many challenges that supply chains are dealing with. However, managing these challenges is possible. The only resolution to all the problems faced by supply chains is Artificial Intelligence or AI. It can help with multiple things related to supply chain management and handling the complexity of supply chain challenges with data and analytics.

Here is a brief list of what supply chains can achieve with the help of AI including increased visibility:

  • Gain end to end visibility across disparate systems and data sources throughout the supply chain.
  • Identify and eliminate blind spots across the supply chain.
  • Proactively predicting and mitigating disruptions before they happen.
  • Examine and prioritize disruptions instantly.
  • Significantly reduce disruptions and cut down the time taken in disruption mitigation.
  • Make available all the data and information that the supply chain professionals need to act fast and with confidence.

Artificial Intelligence is never asleep. It can help you predict disruptions before they take place. AI enables you to gain end to end visibility which is critical to predicting, assessing and mitigating disruptions.

Suppose a company is dealing with the lack of supply chain visibility. Its key supply chain data is maintained in disparate systems and sources. This makes it hard for the company to manage customer orders and mitigate disruptions.

Due to the lack of visibility into inbound deliveries and delays, the company is unable to address customer preferences as efficiently as it should. However, with AI, it becomes easier for the company to compare and correlate data, lying across diverse and isolated sources. This makes it easier for the company to connect all the relevant dots. Now, it can compare and correlate data and have an end to end view of its supply chain in real time.

Now, the managers have the critical information at their fingertips and they can see the status of critical orders quickly. They are also more confident about the data or information they are viewing. Ai enabled smart alerts let the responsible people know that a late inbound delivery could affect a customer order.

AI does not depend only on the internal data sources but also scans external sources like news feed, social media feeds and other external sources to send alerts about external events that may potentially disrupt the supply chain.

In case a disruption occurs anyhow, AI instantly creates a resolution room involving the right people to resolve the situation faster. The final resolution is later archived and then provided by AI as a suggestion if a similar situation occurs in future. AI learns over time, which means it only keeps getting better at what it does. So, over time, the resolutions do not take hours or days but are made possible in minutes with the help of AI.

So, what changes by applying AI to supply chain operations? The first important benefit of applying AI is that the supply chain professionals have access to actionable insights in real time based on which they can proactively assess events and potential repercussions. They did not have access to this kind of information previously. Now, they are armed with the right information which is available to them in real time and they can act quickly and confidently. Previously, all of this data was lying in different sources and comparing data across various sources and generating actionable insight from that data was not possible. However, AI helped bridge the gap and now all the data can be easily compared and based on this information, the supply chain experts can act faster.

Now, the supply chain experts are receiving critical information in real time and with AI driven recommendations, they are able to resolve issues before they can impact customer orders. The end result is that the company is able to provide superior customer experience with the help of an AI powered supply chain. AI leaves no gap or no chance for errors and customer experiences improve a lot. So, this is how AI can completely transform a supply chain and prepare it for disruptions and other risks.

AI can understand and correlate data in a manner that is not possible using other systems. Supply chains are inundated with data but generating actionable insights from them remains impossible since comparing and correlating data across the disparate sources remains impossible without the use of AI.

It is why a large number of companies have decided to switch to the use of AI to revive their supply chains. According to a report, around 55% of Global 2000 OEMs will redesign service supply chains by 2026 using AI. According to a Gartner report, AI is going to have the most solid impact on supply chains by 2025. As per the report, decision making automation had increased from 15% to 48% in the sourcing and procurement function between 2018 and 20211. AI is also predicted to add enormous value to various industry sectors by 2025, which may be about $5 Trillion2. Now supply chain leaders across various industry sectors are using AI based tools to automate decision making.

AI has the ability to bridge a major gap in terms of supply chain management. Increased visibility is critical to managing supply chains and mitigating risks. The lack of end to end visibility in the entire supply chain can be resolved through the use of AI.

Supply chain experts need actionable insights in real time to address various challenges. AI can read, understand and correlate data using both internal and external sources at a rapid pace. It can process the data to provide actionable reports in real time based on contextual analysis of that data.

AI will correlate data and think like a human but at a significantly higher speed and scale. So, it will process tons of data and provide deeper insights to improve visibility across the supply chain. Moreover, AI does not rely on only internal sources of data. It is just as effective with structured data as unstructured data. AI will collect structured data from sources like planning, sourcing, production, warehouse, transport and other systems. It will also process unstructured data collected from news sources, reports and social media feeds. In this way, AI taps into previously untapped sources of data to produce more reliable insights and supply chain intelligence.

However, the biggest benefit in terms of supply chain management comes from its ability to correlate and compare structured and unstructured data. The AI based systems continue to learn and evolve and they will grow more efficient with time. It is possible to train them to understand your supply chain needs better. Over time, they will understand user preferences better.

The AI enabled systems can learn and evolve to the level that they start understanding your supply chain practices in a manner that they can start interpreting demand and risk signals from structured and unstructured data sources. Based on these signals, you can remain alert and keep your team members alert. Supply chain officers can provide recommendations to their staff based on these signals.

Moreover, the supply chain officers can search and query information in AI enabled systems using natural language, which will increase productivity in terms of decision making and prevention of supply chain disruptions. AI will continue to learn from your past actions and decisions, which is an important reason, it grows more perfect with time. At a point, it will start offering you instant insights and recommendations based on your previous best practices.

AI promises to usher in a new era of supply chain optimization with its game changing capabilities.