How Artificial Intelligence Is Revolutionizing Supply Chain Management

Viral Patel
Published 07/28/2023
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AI for Supply Chain ManagementTo remain competitive and succeed in today’s global marketplace, companies need to run their organizations like a fine-tuned engine to sustain growth. With that in mind, businesses that use transformative artificial intelligence (AI) technologies are well-positioned to conquer challenges and better manage their supply chains while improving costs and enhancing efficiency, operations, performance, and the customer experience. One of the most critical ways AI revolutionizes supply chain management is through predictive analytics. AI can accurately predict future demand by analyzing data, allowing companies to optimize inventory levels, streamline supply chain processes, and reduce the risk of stockouts or overstocking. This type of supply chain automation is only possible with AI.

Benefits of using AI in supply chain management

Effective supply chain management (SCM) is essential to optimizing the flow of products and services and streamlining business operations. From procuring raw goods to managing reliable suppliers to automating various warehouse processes to optimizing shipping routes and delivery times, every point in the supply chain must work efficiently to improve a company’s bottom line and ensure a competitive advantage.

Many companies already see the advantages of automating supply chain tasks through AI, including back-office and warehouse logistics, quality checks, inventory management, and supplier relationship management. By leveraging AI in the quality control of supplier management, companies can automate manual and time-consuming tasks, improve accuracy, efficiency, and sustainability, and achieve greener warehouse processes. According to research, 37 percent of businesses, including supply chain companies, already see the benefits of AI solutions. AI will also contribute $15.7 trillion to the global economy by 2030.

When the supply chain is fully optimized with successful SCM, companies are likely to experience these benefits:

  • Decreased operating costs. Companies can lower operational costs by reducing purchasing and production expenses. For example, suppose a grocery store owner buys fresh vegetables directly from the farmer. Eliminating the expense of using a third party to purchase products can save money and vegetables are available in the store faster. Additionally, AI provides data transparency for better supply chain visibility and cost savings.
  • Better productivity and reduced labor costs. Leveraging AI enables manual work to be done more efficiently by automating manual tasks. It’s estimated that 40 percent of the workload during the sales process can be automated through AI solutions. This decrease in human labor reduces operating costs.
  • Improved relationships with suppliers, manufacturers, and distributors. When relationship management works well and all parties, including suppliers, manufacturers, retailers, and planners, work collaboratively, companies can avoid overstock or out-of-stock scenarios.
  • Shorter delivery times and on-time delivery. AI can track shipments and facilitate the on-time delivery of goods by analyzing data and identifying patterns, helping managers make better decisions. Walmart uses AI to analyze sales patterns and optimize inventory levels, reducing product stockouts and getting fresh food to shoppers faster. This leads to enhanced customer satisfaction.
  • Improved transportation network and routes. AI finds the most efficient and cost-effective way to transport goods by analyzing the number of trucks needed, the fuel consumed, and the time it takes to get from point A to point B. For example, UPS integrated AI into its logistics operations to optimize route planning and package delivery. AI also analyzes weather conditions and traffic patterns, helping reduce fuel consumption and enhance delivery automation and accuracy.
  • Reduced risks. AI provides data on warehouse management systems and identifies weaknesses, gaps, and risks. Businesses create a safer work environment and a more efficient supply chain by identifying potential risks and taking proactive steps to correct them.
  • Enhanced decision-making capabilities. AI’s ability to analyze mass data in minutes facilitates critical decision-making. Yet, AI doesn’t replace humans. Instead, it provides increased data visibility and insights that facilitate faster, more accurate, and more precise decisions.



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AI disadvantages

While AI has myriad benefits for supply chain management and applications, it’s not without challenges. As such, it is essential to understand some of the drawbacks associated with the use of AI in supply chains. These include:

  • Biased algorithms. Design flaws or erroneous data sorted into algorithms can lead to limited software and technical artifacts. AI duplicates societal biases for race, gender, and age, which increases social and economic inequalities. If data is not representative of the entire supply chain, it can lead to skewed results and poor decision-making.
  • Disinformation. With deep fakes and online bots spreading disinformation, society faces inconsistencies between reality and fiction, destabilizing trust in social media, news sources, and political institutions. During the COVID-19 pandemic, misinformation about lockdowns caused people to rush to stock up on essential items, causing shortages, increased demand, and a broken supply chain.
  • Lack of transparency. AI input data can have errors or may need to be better cleansed. Data engineers could inadvertently select biased data sets and generate scenarios that could create poor visibility and quality. A lack of transparency in a supply chain can damage customer loyalty and strategic partnerships.
  • Cybersecurity risks. According to Terence Jackson, a chief security advisor at Microsoft, attackers can use generative AI to create “new and complex types of malware, phishing schemes, and other cyber dangers” that result in data breaches, financial losses, and reputational risks. A compromised enterprise computer system can bring a supply chain to a screeching halt and result in the loss of valuable customer relationships.
  • Loss of human expertise. AI should not replace skilled workers and eliminate jobs, but it can be used for dangerous, manual, or repetitive work. The importance of institutional knowledge and experience cannot be undervalued.

The human factor is vital when using AI

While leveraging AI technology is advantageous, the human factor remains crucial to success. Humans contribute unique qualities to business processes and operations, such as ethical judgment, creativity, emotional intelligence, and accountability. AI-based machines are faster and more accurate; however, humans bring intuition, emotion, and cultural sense, adding greater significance to the workforce. Uniting AI and human employees leads to more effective decision-making and innovation in various industries. AI should only enhance human qualities, not replace them.

Incorporate AI for faster and more effective supply chain systems

Companies that have successfully applied the power of AI have realized notable improvements in SCM, resiliency, and sustainability. AI is a powerful game changer as it addresses the opportunities and challenges of business functions while providing visibility into operations and the capability to analyze mountains of data. AI can be valuable, and a return on investment can be attained if the technology investment matches organizational changes, business process updates, digital transformation, and employee skills training.

About the Author

Viral Patel is a senior logistics analyst with more than 15 years of hands-on experience in the areas of logistics and supply chain operations management. During her career, Viral has demonstrated a unique ability to analyze an organization’s management procedures, identify deficiencies and potential opportunities, and develop operational solutions to increase reliability and improve productivity. She has a master’s degree in technology management and specialized in global project and program management at the University of Bridgeport. She also earned a bachelor’s degree in management studies from the University of Mumbai. For more information, contact


Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.