Supply chain AI: AI for smart distribution center operations

Distribution center operations require unprecedented agility and accuracy to keep pace with customers' increasingly high expectations. Picking, packing, and shipping must all go smoothly, and deliveries must go out faster than ever. However, labor challenges surrounding employee recruitment and retention make it challenging to meet today's elevated service standards continuously.

Artificial intelligence (AI) is transforming several industries, including distribution and logistics. Supply chain AI can help distributors solve these problems in multiple ways, whether forecasting demand more accurately or proactively planning for their workforce needs throughout the year. Learn how distribution centers can use AI to improve productivity, operate with increased precision and earn customer accolades.

Six AI use cases for distribution centers

Distribution centers can use AI to enhance efficiency and productivity in multiple ways. Here are six of the most impactful use cases:

1. Demand forecasting and inventory optimization

• Predictive analytics: AI algorithms analyze historical sales data, market trends and even weather patterns to forecast future demand with greater accuracy.
• Automated replenishment: AI can automate purchase orders based on demand predictions. This allows distributors to optimize inventory levels, minimizing stockouts and excess inventory.

2. Warehouse automation and robotics

• Automated mobile robots (AMRs): AI-powered robots can help automate the movement of goods within the warehouse, improving speed and efficiency. According to a recent research study, 19% of respondents have already deployed this technology and 25% will do so within the next 24 months.¹
• Robotic picking and sorting: Robots equipped with computer vision and machine learning can identify, pick, and sort items with greater accuracy and speed than their human counterparts.
• Connected fork trucks: AI-enabled fork trucks equipped with sensors can provide real-time location tracking, monitor battery life and maintenance requirements, and in some cases, autonomously navigate specifically delineated routes within warehouses.

3. Smart warehouse management

• Real-time visibility and tracking: According to the study, 35% of distribution companies have already deployed either radio-frequency identification (RFID) or Internet of Things (IoT) inventory tracking, and 13% plan to do so within the next 24 months.²
• Predictive maintenance/condition-based maintenance: AI algorithms analyze sensor data from equipment to continually assess conditions and predict potential breakdowns, enabling proactive maintenance and minimizing downtime.

4. Labor management and optimization

• Next task directions: Generative AI can proactively communicate next task instructions to connected employees.
• Task allocation and optimization: AI can analyze worker performance data and optimize task allocation, ensuring the right connected workers are assigned to the most suitable tasks.
• Workforce planning and forecasting: AI helps predict future labor needs based on anticipated demand fluctuations, allowing for proactive and connected workforce planning.

5. Enhanced security and safety

• Surveillance and anomaly detection: AI-powered cameras can monitor the facility for suspicious activity, identifying and alerting security personnel to potential threats.
• Safety monitoring & accident prevention: AI can analyze worker movements and identify potential safety hazards, helping to prevent accidents and injuries.

6. Improved shipping and logistics

• Route optimization: AI algorithms can optimize delivery routes in real-time, considering traffic conditions and other factors to minimize delivery times and fuel costs.
• Carrier selection and management: AI can analyze historical carrier performance data and select the most efficient and cost-effective carrier for each shipment.

Benefits of AI for distribution center operations

Distribution centers can use AI to:

• Reduce costs and increase profitability
• Improve efficiency and productivity
• Enhance accuracy and minimize errors
• Increase customer satisfaction
• Create a safer working environment

Supply chain AI: AI use cases require modern and reliable network connectivity

All of the AI use cases discussed above heavily depend on reliable network connectivity that performs well across the entire enterprise facility—whether indoors or outdoors, throughout large open spaces, in hazardous environments and beyond. Inconsistent and non-secured connectivity would hamper AI's ability to deliver the expected results. This is especially true for assets, products and resources that are in motion, such as one would find in a distribution center.

Although distribution centers have traditionally relied on legacy wireless technologies to carry out their operations, these common approaches may not be able to support AI use cases. 61% of distribution companies that responded to the study said that they were dissatisfied with Wi-Fi reception inside the building, for example.³ Additionally, Wi-Fi may face a few issues in harsher industrial enterprises: poor coverage, unreliable quality of service (QoS) and mobility hand-off issues between access points, to name a few. One critical problem is the presence of 'zombie zones,' or areas with poor connectivity in warehouses where connectivity disruptions can impact robotics, inventory management, order processing and communication.⁴ The total cost of ownership (TCO) of a Wi-Fi network can add up, especially in large outdoor deployments that require a high density of Wi-Fi access points.

Fortunately, distribution centers now have a modern and advanced network solution that can help enable their AI requirements. Private wireless is an LTE/5G network that can exclusively cater to a distribution center's precise wireless needs. A private 5G network creates a highly reliable, consistent and secure connectivity environment to support a large number of connected devices, a high data volume and high-fidelity applications in a variety of operating contexts. Private 5G can also help eliminate "dead spots" for coverage. These advantages favorably compare to traditional 802.11 wireless deployments that do not sufficiently enable real-time communications, mobile devices and automated robotics.

An even greater role for AI in distribution centers

As illustrated above, distribution centers can help boost productivity, enhance accuracy, and earn increased customer satisfaction. As technology continues to evolve, AI could play an even greater role in optimizing distribution center operations and shaping the future of supply chain logistics. In fact, 84% of survey respondents agreed that AI will be necessary to remain competitive in the future.⁵ Accordingly, distributors that begin embracing today's supply chain AI use cases will find themselves well-positioned to take advantage of AI's transformative potential in the coming years.

Learn more about Verizon's distribution and logistics solutions.

The author of this content is a paid contributor for Verizon.