16, Jul 2024

How Gen AI Tools Improve Supply Chain: Pros and Use Cases of Intelligent Systems

Discover the impact of Generation AI tools on optimizing supply chain management. Learn how intelligent systems streamline logistics, enhance efficiency, and drive cost savings. Explore real-world use cases and the evolving role of Generative AI.

Gen AI Tools in Supply Chain

ABOUT THE AUTHOR

Dmitry Boyko, Android Team Lead

Serhii Stavichenko,
CTO

Serhii Stavichenko, CTO

Serhii knows everything about project architecture, data science, and machine learning. His superpower is translating clients' business needs into top-notch technical solutions.

Supply chain management is an essential part of businesses. This process helps to control the flow of services or goods from the manufacturer to the purchasers.

The huge volume of data in supply chains places a heavy burden on company employees. Naturally, companies are looking for ways to optimize this process. Instead of human work, artificial intelligence can process data hundreds of times faster and more efficiently. Implementing supply chain generative AI tools increases supply chain productivity and better automation. Ventures also benefit from optimized order tracking and processing and more.

In this article, you will discover how gen AI tools influence supply chain management. You will understand why companies are actively using artificial intelligence and exactly how it can improve work processes.

Main Challenges in the Supply Chain

The supply chain may fail for various reasons, including product limitations, logistics risks, and supplier unreliability.

Main challenges in the supply chain

Lack of supply chain visibility

To accurately track the movement of goods to customers, companies need access to real-time analytics. Otherwise, there will be delays and unnecessary budget costs.

Risks with logistics

Transportation management and logistics are the most resource-intensive for businesses. These processes typically consist of fixed contracts with third-party logistics providers. In case of failures in the supply chain, the company takes responsibility for compensating the damage to the end client.

Insufficient inventory

Every supply chain manager aims to balance shortages and surpluses. It is important to effectively process information about past customer transactions. This helps to predict the optimal inventory balance.

Suppliers control challenges

Approximately 80% of supply chain failures occur at lower-tier suppliers. Companies face this problem, especially when geographic distance results in a lack of visibility. Businesses need to be able to rely on their suppliers to provide consistent prices and reliable quantities.

Benefits of Using Generative AI for Supply Chain

Artificial intelligence can significantly help enterprises to develop, increase team productivity, and attract customers. For supply chain management, gen AI is of great importance, because in this field there are big risks for excess costs due to insufficiently optimized processes.

Higher productivity

The use of AI helps ventures reduce manual tasks for employees, process data faster, and optimize production cycles. This results in more reasonable resource distribution and lower downtime.

Customer satisfaction

Consumers appreciate the company's reliability and speed of order fulfillment. AI tools can speed delivery, optimize transport logistics, and increase supplier quality control.

Increased profit

By using AI to optimize their supply chain, companies benefit in the long run. Tools based on trained neural networks will help businesses save budgets. They prevent businesses from risks, including unreliable suppliers or transport delays.

Use Cases of Gen AI in the Supply Chain

Artificial intelligence in supply chains allows the application of powerful optimization capabilities, reduces costs, and increases productivity. Below we will consider the main supply chain AI use cases.

Use cases of gen AI in supply chain

Better inventory management

Long-term business goals for companies may include improving profit and loss statistics. Gen AI models will help improve monthly execution time and reduce downtime.

Cost-efficient product delivery

Generative artificial intelligence will help companies find the most optimal delivery routes. This technology selects modes of transport distribution centers and thus reduces costs. Logistics companies can apply gen AI to manage truck fleets by gathering and analyzing data from GPS traffic updates. On-time delivery increases customer loyalty and lets businesses get more profits.

Accurate demand forecasting

Customer preferences tend to change, which affects market demand. To meet new requirements, companies need gen AI models. They will analyze data and create accurate demand forecasts.

Increased sustainability

Enterprises that use gen AI can make processes more sustainable by optimizing the transportation of goods. AI models can detect the most suitable roads to achieve more reasonable fuel consumption and gas emissions. This impacts the support of eco-friendly initiatives.

Far-sighted risk management

Generative artificial intelligence can help you find and track patterns in supplier reliability and anticipate other failures. These can be problems on the roads or in geopolitical situations. This way, companies can diversify risks promptly by effectively redistributing work.

Supplier relationship management

Generative AI can effectively evaluate supplier quality and cost factors. AI models analyze interactions with them, identify risks and opportunities for improvement, and support proactive supplier management.

Firms that Successfully Implement Generative AI in Supply Chain

According to the McKinsey survey around one-third of companies now apply generative AI for their business optimization. Amazon, Walmart, Maersk, UPS, and many other retail giants have already implemented AI in their supply chain processes. With artificial intelligence, USP can reduce fuel costs. For example, Walmart obtains predictions about demand. Amazon engages clients and more. The fact that such large companies use generative AI tools proves their effectiveness.

UPS uses generative AI in supply chain

It is one of the largest package delivery ventures in the world, with a fleet of more than 125,000 vehicles and more than 500 aircraft. UPS provides complex logistics capabilities, cargo transportation, and supply chain management services.

This company is committed to sustainability and aims to achieve carbon neutrality by 2050. The use of gen AI helps the company reduce carbon dioxide emissions by optimizing delivery and reducing fuel costs.

Walmart applies supply chain generative AI

Walmart is the largest American retail chain that sells both industrial and food products. This retail giant has long used AI tools to manage logistics and inventory, which is necessary with such volumes of trade. With the help of AI tools that predict market demand, Walmart can learn about customer preferences in advance.

Also, thanks to neural networks, this company optimized inventory levels and minimized the risks associated with product shortages. AI has significantly helped the company reduce costs and improve customer satisfaction.

Amazon leverages the power of AI solutions

This huge e-commerce marketplace has successfully used artificial intelligence tools for end-to-end supply chain solutions. Generative AI for supply chain helps Amazon to speed up operations and reduce costs. The AI technology optimizes logistics and improves customer satisfaction.

By incorporating AI, Amazon's delivery is streamlined and efficient. But the company does not stop there. It makes investments in the latest technologies such as OrderPulse or SupplyChainIQ to maintain low prices and high-quality service. These conditions are optimal for both sellers and buyers.

Gen AI Tools for Supply Chain Optimization

Below you can see some of the supply chain AI companies that offer powerful tools for supply chain management to optimize the processes.

Logility

This powerful tool helps global businesses with complex supply chains to respond quickly to changing market conditions. Companies can use this platform to enhance inventory management. Logility also offers demand forecasting to streamline the supply chain.

Logity

Core features:

  • Providing advanced analytics generated by AI
  • Optimizing inventory with a reduction in obsolete stocks and effective new goods management
  • Demand forecasting
  • Integrated business planning
  • Sending alerts for the lack of inventory, stockouts, and replenishment cycles

BlueYonder

It is a modern omnichannel planning platform with which enterprises can enhance order fulfillment. BlueYonder helps businesses receive accurate demand predictions and, based on this information, enhance customer experience.

BlueYonder

Core features:

  • Offering AI-based demand forecasting and predictive analytics
  • Improving visibility from purchasing to delivery
  • Helping with stock-level optimization

IBM Watson Supply Chain

This AI tool from IBM helps optimize supply chains with predictive insights. Considering the provided information, enterprises can address emerging disruptions and prevent them. This platform helps drive sustainability, resilience, and efficiency in the supply chain.

IBM

Core features:

  • Giving predictive insights
  • Providing visibility in real-time
  • Offering cognitive automation
  • Simplifies collaborative efforts among all stakeholders

Supply Chain Optimization for Medical Business by Requestum

Supply chain optimization is necessary not only in retail commerce but also in such sectors as medicine. At Requestum, we helped a healthcare startup reach the next level by optimizing its supply chain.

B2B GMP, a UK firm serving the medical CBD and THC market, selected us to develop a CRM-like platform to manage the supply chain and simplify access to medical CBD and THC products. Such drugs are needed to treat complex diseases such as cancer.

B2B GMP

This medical enterprise requires a centralized solution to connect industrial suppliers with pharmacies and clinics. Because of supply chain delays, the patients experienced issues in treatment, which impacted their recovery process. Our team has created a robust platform so vendors and healthcare specialists can collaborate effectively.

Conclusion

Companies using AI in supply chain management will become more sustainable and optimize their cost structure. AI technologies will help build more efficient supply chains when planning, sourcing, manufacturing, or transporting products. Organizations are now forced to consider the capabilities of AI updates and implement them or risk being left behind in the market.

The Requestum team has vast experience developing top-quality AI solutions. These projects help businesses improve their work processes and attract customers. So, if you have any questions or think about creating an AI solution, feel free to contact us.

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