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AI in Logistics Management: The Moment Has Come

AI in Logistics Management: The Moment Has Come

The ever-expanding field of artificial intelligence is leaving an indelible mark on logistics industry. DHL identified in its Logistics Trends Radar report that AI and machine learning as key technologies driving logistics innovation with an ability to rapidly make sense of massive data sets with automation of operational processes. The AI is transforming the reality of this business, that is a fact we all must accept.

Here are 3 Ways AI is Transforming Logistics Management

1. Predictive Logistics

With its ability to gather and analyze thousands of disparate data points, AI can help you solve a problem you don’t know is there. Combining data from historical events, current environment, and future expectations, AI enables businesses to shift from reactive to proactive decision making. With AI technology, shippers can manage disruptions (like weather), reduce downtime, and effectively plan and budget their logistics spend and operations. More impactful than dealing with disruptions, AI-enabled logistics platforms allow organizations to drive efficiency and profitability from daily operations.

2. Optimization Events

AI is being used to make faster and smarter decisions that optimize carrier selection, rating, routing and quality control processes. The abundance of data, sophisticated algorithms, and dynamic business rules helps move shipments from point A to point B, C, and D, using the most efficient, fastest route. In the past, it could have taken up to six months to thoroughly understand the unique features (best- and worst-case transit time, the impact of weather and other factors) of specific routes. Today, analytics based on AI can examine large sets of data in seconds and create simulations that match shipper demand with carrier behaviors like capacity, service capabilities and backhaul opportunities to determine the best combinations of carriers and lanes for delivering loads.

3. Recommendation Engines

In logistics management, many repetitive tasks can be made more efficient through automation. Using AI computing techniques, like machine learning and natural language processing, we can teach systems to recognize patterns in data, and based on its findings, issue a recommendation or action. Over time, self-learning enables logistics solutions are continuously improve operating algorithms and deliver more informed suggestions that help shippers automate logistics decisions and increase the efficiency of business processes.

These kind of solutions incorporate real-time information on weather, seasonality, traffic, and other data inputs to recommend the best solution for each shipment. Rather than spending hours on repetitive tasks, AI enables businesses and their employees to focus their time on higher-value projects that help transform and grow their businesses.

How to Leverage the Power of AI in Your Logistics Operations

As companies continue to emphasize the impact logistics has on earnings and customer loyalty, they increasingly turn to innovative technology and automation for practical solutions. Logistics leaders should equip their business and teams with technology, like TMS services, which centralizes freight data, integrates business systems data, and leverages AI, machine learning and predictive analytics to create operational efficiencies and make better business decisions.

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