How AI Can Mitigate Supply Chain Issues

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The supply chain crisis has been much in the news of late. It’s not difficult to understand why. The crisis has had a profound impact across industries and throughout the global economy. It has contributed to surging prices, layoffs, productivity declines and empty store shelves.

However, there is hope on the horizon and it is coming in the form of Artificial Intelligence (AI). The technology is improving the supply chain in a myriad of ways, from optimizing inventory management to enhancing warehousing and storage processes to automating critical elements of the supply chain. If properly executed, supply chain AI has the ability to improve logistics drastically at a time when every minute counts. 

Early adopters of AI in supply chain management saw a decrease in logistics costs of 15%, an increase in inventory levels of 35%, and a boost in service levels of 65%. This automation and optimization could be the difference between a business thriving or floundering when supply issues arise.

Optimizing inventory management

Inventory management is often both an art and a science. It requires decision-makers to maintain constant oversight of existing inventory levels while anticipating future needs. It mandates that managers cultivate sufficient knowledge of market trends and customer behaviors to be able to identify the sweet spot in inventory planning, ensuring there are always sufficient supplies of necessary products and materials while preventing surpluses and waste.


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This is a challenging process, one that can have significant ramifications for the supply chain, as effective inventory management prevents clogging the supply line with rush shipments or with superfluous transports.

This is where the power of AI shines through. AI-driven technologies can provide continuous surveillance of warehouse, retail and industry inventories, and can autonomously order new materials when supply levels reach a critical level. 

Perhaps even more significantly, the machine learning (ML) capabilities of AI technologies mean that decision-makers will have more timely, relevant and plentiful data with which to plan inventory needs. This includes robust capabilities for accruing data on market trends, customer behaviors and related metrics to predict short-term and long-range supply needs.

Supporting transport, warehousing, and storage

Another significant challenge impacting the supply chain is the necessity of ensuring not only that materials reach their intended destination in a timely manner, but that supplies are in optimal condition when they get there. 

This is no mean feat, particularly when transporting fragile materials across a continent or around the world. AI-powered sensors, though, can track individual shipments, as well as discrete items within each shipment, at every phase of transport, reducing the risk of lost or misdirected shipments.

However, this is only the beginning of the story, as AI sensors aren’t just adept at tracking location. They can also provide accurate, comprehensive, and relevant data on environmental conditions across the entire supply chain, including warehousing, storage, and transport containers. 

This is an especially important asset for reducing risk in cold chain shipping and storage. Materials that need to be maintained at a specific temperature or humidity level — such as perishable foods, medications, or certain electronics — may be rendered dangerous or unusable if there is a failure in a cargo container’s or warehouse’s refrigeration systems. 

AI sensors can send alerts to stakeholders when environmental conditions begin to approach unsafe parameters, allowing them to take action before inventory is lost. This capability can also significantly increase trust among stakeholders by enhancing visibility and transparency across the supply chain.

Automating processes

Because ML enables AI to “learn” from each action it performs, the capacity to automate processes increases substantially over time. This means that not only are workflows less dependent on human labor, but they are more accurate and reliable than the product of human work. 

Human error is a simple fact of life. People get tired. They make mistakes. They have physical and cognitive limitations. AI, however, never tires. 

It generally only makes mistakes when it has been programmed incorrectly. Its “intelligence” increases exponentially over time. What this means is that when you automate elements of the supply chain using AI technologies, you’re going to get greater efficiency, accuracy, and productivity than even the most skilled humans.

In addition, as the COVID-19 pandemic has shown us that human vulnerabilities can jeopardize not only their well-being but the health of the supply chain. Pervasive and prolonged lockdowns threw the entire global economy into turmoil, decimated once-successful businesses, and threatened the livelihoods of millions of workers.

Using AI to automate the supply chain means that work can continue to flow, businesses can continue to operate, and products can continue to be produced and consumed should another pandemic or other global crisis emerge. If implemented correctly, business leaders and employees may never again have to face the terrible choice between their health and safety and their career and income.

Making business decisions with AI 

Of course, implementing these AI practices is easier said than done. For one, there may be overhead costs to consider. For another, employees may be concerned that new AI systems will take over their jobs, especially if they work in the industrial sector. To address such concerns, it’s best to approach AI with the following steps:

  • Learn more about AI: As a business leader, the more you understand AI, the more equipped you’ll be at pointing out solutions you can apply to your business. You may even create new solutions of your own. As such, stay up to date with the latest AI technology announcements.
  • Pitch a new AI system to a team of leaders: This team may be your corporate leaders or simply a managerial team. Within this pitching process, you’ll also address any overhead costs. If you find these costs can’t be budgeted for, you can either go back to the drawing board to fit them in or scrap the idea altogether.
  • Announce your plans to your employees: Approach this with sensitivity and be open to feedback. Most automation is typically for the betterment of employees and their safety, so it’s best to also communicate this.
  • Be adaptable: You’ll inevitably have to change plans at several points in your pitching process. If this happens, be open to new ideas, especially if it’s to solve supply chain issues.

Even if this pitching process falls flat, hold out hope. AI is still a relatively new technology, and it may take time for your company and your employees to accept it with open arms.

The takeaway

The ongoing supply chain crisis has taken a profound toll on businesses, workers, and consumers alike. However, AI innovations may make such crises a thing of the past. AI technologies are proving highly beneficial across all stages of the supply chain. They optimize inventory management, enhance warehousing and storage and support process automation — all to spur efficiency and productivity, prevent human error, and protect the supply chain from future crises. 

Charlie Fletcher is a freelance writer covering tech and business.


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