A solid supply chain management strategy gives you the flexibility to navigate potential challenges and maintain a great relationship with your customers. Artificial intelligence (AI) is becoming a key component in supply chain management. Read on to learn more about the future of AI in supply chain operations and how you can make it work for your business.
How Is AI Changing Supply Chains?
The potential of AI is helping businesses across logistics and manufacturing enhance customer service in multiple ways.
Inventory Management
Managing inventory with AI lets you keep the right products, parts, or raw materials on hand to meet customer demand without paying to store excessive stock. AI-powered inventory management programs can analyze historical data and generate valuable insights, beyond demand forecasting, for decision-making. Plan your warehouse to pack and store inventory to speed up the picking and packing process.
AI in warehouse management will also notify you when stock reaches a critical point, or automate purchase orders when stock reaches a certain level. Your supply chain managers don’t have to do manual inventory counts as often, and they can be sure there will be enough product in stock to meet customer needs.
Logistics and Route Optimization
AI-powered supply chain technology uses data analysis and machine learning to optimize logistics and shipping routes. Route management software analyzes traffic patterns, fuel costs, weather conditions, and other data to plan the fastest, most cost-effective shipping route.
These systems also optimize delivery routes based on a driver’s other packages, their due dates and times, and locations. Your drivers can make more deliveries instead of driving across town multiple times, wasting time and fuel.
Risk Management
Supply chain disruptions are unavoidable, but AI supply chain technology can help you anticipate and mitigate them sooner. AI will assess internal and external supply chain pressures including supplier performance and capacity, geopolitical issues, weather conditions, cyber threats, and other potential disruptive factors, allowing you to make backup plans.
It also analyzes workplace safety data and other compliance metrics to keep you on top of industry regulations.
Demand Forecasting
Using machine learning, AI will analyze historical data, market trends, and seasonal insights to identify patterns that predict demand. It can also spot patterns in data that highlight demand anomalies, price fluctuations, and potential stockouts.
Use this data to manage stock levels and meet customer demand. If your AI supply chain management system notifies you of potential price increases, stock up while the price is still low.
4 AI Supply Chain Technologies and Trends
Supply chain professionals utilize these common supply chain technologies to enhance their operations.
Machine Learning
Machine learning is a component of AI-powered technology that uses algorithms to analyze datasets, identify patterns, and make predictions. As you enter more data into the system, its algorithms change and start interpreting data more accurately.
Machine learning is more effective when you feed good data into your AI system. Make sure you format all your data the same way and remove duplicate information before entering it into the system. Newer systems featuring agentic AI in supply chain operations will use machine learning and natural language processing to set their own goals and make their own decisions.
Digital Twin Technology
A digital twin is a realistic replica of a physical object, system, or process. If you work in manufacturing, you might use digital twin technology to make design changes to a digital model before making the physical product.
In supply chain management, digital twin technology lets you replicate the whole supply chain. You can run various models to simulate how your changes will impact deliveries and make decisions based on the results.
Robotic Process Automation (RPA)
RPA refers to using AI-powered software to manage repetitive tasks. RPA programs take over data entry, report generation, inventory management, and other tedious tasks. This reduces human errors and frees up your team members for more challenging tasks.
An RPA can automatically check a customer’s packing slip against an order, generate a shipping label, and update your inventory system. Your customers are more likely to get the right order on time, which improves customer satisfaction.
Predictive Analytics
In supply chain management, AI-powered predictive analytics inform everything from inventory management to logistics. AI for data analytics will identify patterns in volumes of data that help you manage potential risks or streamline your operations. This data offers better supply chain visibility to guide how you plan and manage your workflows.
Challenges of Combining AI and Supply Chain
While AI brings many benefits to supply chain management, it does present issues you need to consider.
Data Privacy and Security
Because AI assesses actual customer data, you risk compromising your customers’ privacy. AI also gives hackers new ways to access your systems and disrupt operations. Mitigate these risks by removing any personal information and identifying details from the data so the system is only assessing transactions.
Put security protocols in place including authentication and other access controls. Always update your systems with the latest patches to manage security risks.
Technical and Implementation Challenges
Your new AI supply chain management system may not integrate with your existing systems. In this case, you would have to enter historical data manually, which is time-consuming. You also need high-quality data that is complete and accurate.
Workforce and AI Literacy
Adopting AI in supply chain management isn’t always the most popular choice. Some of your team members may struggle to adapt to AI-powered technology. The best way to manage this challenge is to roll out your implementation. Have your most tech-savvy team members use the system first and then help train other team members who learn more slowly.
The Role of Humans in AI Supply Chain
While AI can make supply chain planning and management more agile, it’s not meant to replace your human workforce. AI doesn’t have compassion and other human emotions needed to manage customer and vendor relationships. It’s also not as effective during a crisis.
AI might be able to identify potential risks, but in an emergency such as the Baltimore bridge collapse, you need people who can assess the situation and execute a plan.
Enhance Your Supply Chain Operations With AI
Surgere offers AI supply chain solutions that work together to improve your supply chain operations. Our supply chain intelligence works with Power BI to create clean, visually appealing reports to guide your decision-making. It works in tandem with the IoT and other technologies to improve your supply chain.
Contact us today to learn more.
