[special_heading title=”AI for Logistics and Trucking Transportation – Part III: Implementation” subtitle=”” c_margin_bottom=”0px” font_size=”32px” font_weight=”700″ text_transform=”none” subtitle_fs=”20px”]

In our last two articles, we considered the challenges that the logistics industry is facing and how these challenges present opportunities for AI. Already, some supply chain leaders are making good use of AI to transform operations and are gaining a competitive advantage.

Today, we’ll take a look at some of the ways how AI is being implemented in the logistics and trucking transportation industry.

Predictive Logistics

AI can be used to gather and analyze millions of disparate data points and this allows businesses to address undiscovered problems. By combining current data with historical events and future expectations, AI can help businesses move to predictive decision making.

Already, several companies use AI-enabled logistics platforms to reduce downtime, manage disruptions and drive operational efficiency. Shifting from reactive logistics to predictive logistics allows supply chain companies to increase profitability from operations.

Recommendation Engines

There are several repetitive tasks in the logistics industry. Supply chain companies can make use of AI techniques such as natural language processing and machine learning to automate repetitive tasks.

By recognizing patterns in data through sophisticated algorithms, shippers can automate logistics decisions. Not only does this increase the efficiency of business processes, but it also enables logistics providers to improve business operations and deliver informed recommendations.

Optimization Events

Another way in which AI is being used in the logistics industry for smarter and faster decision making. Businesses are making use of AI to optimize quality control processes, routing, rating and carrier selection.

The abundance of business data, sophisticated AI algorithms and flexible business rules enable logistics businesses to optimize events. Analytics based on AI can be used to examine large data sets in a matter of seconds to match demands with carrier behavior to determine the best combinations of lanes and carriers for delivering loads.

More and more companies in the logistics industry are turning towards AI and automation to devise practical solutions. Give the rapid proliferation of devices and the immense speed of data growth, supply chain companies should look to embrace AI to keep pace with other industries.

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[vntd_button label=”Part I: AI – Challenges” align=”right” url=”url:https%3A%2F%2Finnovoco.com%2Fai-logistics-trucking-challenges%2F|title:AI%20for%20Logistics%20and%20Trucking%20Transportation%20%E2%80%93%20Part%20I%3A%20Challenges||”]
[vntd_button label=”Part II: AI – Opportunities” align=”right” url=”url:https%3A%2F%2Finnovoco.com%2Fai-logistics-trucking-opportunities%2F|title:AI%20for%20Logistics%20and%20Trucking%20Transportation%20%E2%80%93%20Part%20II%3A%20Opportunities||”]