The Growing Role of AI in Supply Chain Management

With the increasing complexity of supply networks, more and more organizations are turning to artificial intelligence (AI) as a solution. According to a recent MHI survey, while only 17% of companies currently use AI, nearly 45% plan to integrate it into their supply chain by 2027.
The survey revealed that almost 50% of organizations believe that artificial intelligence (AI) can potentially disrupt supply chains and provide a competitive advantage in 2022.

AI, which involves the use of machines to perform tasks that would typically require human intelligence, is increasingly being integrated into supply chains to help managers gain greater control over supply chain operations across all tiers.

The primary objectives of artificial intelligence (AI) in supply chain management include the following:

1. Enhancing supply chain visibility.
2. Predicting potential outcomes or disruptions.
3. Identifying data patterns that offer valuable insights and aid in decision-making.
4. Automating supply chain processes.

Artificial intelligence (AI) can be integrated into almost every aspect of the supply chain, from purchasing raw materials to distributing finished products to customers. AI applications in the supply chain work together to improve transparency, efficiency, flexibility and profitability.

AI’s Advantages in Supply Chain Management

The advantages of artificial intelligence in supply chains are vast and will continue to rise. Here are a few examples of how organizations currently benefit from using AI tools in their supply chains.

More precise planning

AI is routinely utilized in supply chains to produce accurate, data-driven forecasts. For example, artificial intelligence-driven demand forecasting is more precise than human forecasting, allowing supply chain managers to:

• Optimize inventory levels to meet consumer demand while ensuring safety stock and reducing storage costs.
  Maintain optimal inventory levels across all geographic regions.
• Forecast the appropriate amount of raw material supply to minimize waste.
• Prepare for fluctuations in demand.

Implementing Artificial Intelligence in Your Supply Chain: Challenges and Solutions

There are several challenges associated with implementing artificial intelligence in the supply chain, including:

• High initial investment costs: Although the cost of AI technology is decreasing as technology advances, implementing AI still requires the appropriate hardware, software, and expertise to run and manage it.
• Education and hiring costs: Implementation costs include training staff to use new AI-enabled technologies and/or hiring new employees with the necessary skills.
• Compatibility: AI has specific use cases in supply chains, making solutions particularly suitable for some supply networks but not yet beneficial for others.

Questions to consider before implementing AI technologies in your supply chain:

• Examine your existing supply chain: What are your current supply chain’s bottlenecks? How is everything going?
• Set specific objectives: What are your objectives? What AI technologies can you use to support these objectives best?
• Examine the estimated return on investment (ROI): What are the costs associated with implementing AI technology? What are the anticipated cost savings or benefits?
• Define the following tracking metrics: How will progress toward these objectives be tracked?
• Prepare your team by doing the following: Is your team ready for this change? Do you need to hire outside IT experts?
• Make a plan: Is your AI strategy scalable? How do you plan for ongoing improvement?