Artificial intelligence is not just another technological advance; it has revolutionized everyday life and is accelerating the evolution of all industries, including logistics.  Starting from the planning stage, using AI combined with big data makes companies more dynamic by inferring users’ intentions to consume certain products, meaning they can now anticipate market demand. In addition, they can adapt their logistics early and manage them accordingly to avoid both understocking and overstocking, thus saving resources.

First Mover Advantage 

Similarly, companies constantly strive to gain an advantage over their competitors in the ever-evolving business world. One way to do this is to secure a “first mover advantage,” i.e., the benefits that accrue to a company that is the first to introduce a new product or service to the market.

There are several reasons why being a first mover can be advantageous. First, a company can establish itself as an industry leader and build name recognition before competitors enter the market, making it easier to gain customers. Secondly, first movers can often charge higher prices for their products or services as they have no direct competition. This can lead to higher profits and market share. Thirdly, first movers can achieve a learning curve advantage. Because they are first to market, they can identify and fix problems with their product or service before competitors can. This can give them a significant advantage in terms of quality and efficiency.

However, some risks are associated with the role of the ” first mover” – the risk of failure, higher costs with R&D investments, and susceptibility to imitation. Despite these risks, first-mover advantage can be a powerful tool for companies to exploit it successfully. Companies that recognize and exploit new market opportunities early are often well-positioned for long-term success.

One classic example of a company that has successfully leveraged a first-mover advantage is Amazon. Amazon was among the first to sell books online. This enabled Amazon to capture a large share of the online book market early on and become the leading e-commerce retailer.  Automated Warehouses are the heart of logistics, and their processes present major challenges and opportunities. By using artificial intelligence and management software with applied robotics, it is possible to automate operations such as the transportation and placement of products, allocating only the necessary resources for each task. There are even “smart warehouses” where artificial intelligence enables the visualization of object data. It is possible to automate virtually all day-to-day operations in a warehouse.

AI In Logistics

AI has helped solve logistics-related problems. Artificial intelligence provides models with a more detailed description for solving logistics problems, and when testing and simulation steps are added, their validation is closer to reality. In transportation, for example, combining artificial intelligence with analytics and big data helps reduce costs. This also helps to provide relevant information that improves the company’s sustainability indicators. It helps with warehouse and inventory management. When SKUs are managed in inventory, AI can locate products in real-time to monitor sales, know inventory status, predict demand needs, and detect errors or fraud in the supply chain.

It enables you to keep track of vendors. Supplier delivery delays directly affect the supply chain’s effectiveness and productivity. Using artificial intelligence and analytics, it is feasible to respond to and even foresee these possibilities, offering a report on what could happen along the entire chain. Building digital twins that can conduct diagnostic and prognostic activities is one example.

Businesses incorporate AI into all of their processes: in warehousing, it is utilized to automate systems that conserve and manage space intelligently while also minimizing maneuvering time; and in transportation, businesses solely rely on route optimization, risk management, and fleet maintenance systems.

Third-Party Logistics And AI 

Third-party logistics (3PL) providers increasingly rely on artificial intelligence (AI) to utilize existing data and gain a competitive advantage. Using AI, 3PLs can gain insights from their data that help them improve their operations, reduce costs, and provide better customer service. Third-party logistics providers (3PLs) play an important role in the logistics industry by offering warehousing, transportation, and fulfillment services to businesses of all sizes. 3PLs use shipping barcodes to manage and track packages as they transit through the supply chain, ensuring they arrive on time and in good condition.

AI can be used in a variety of ways to improve 3PL operations:

  • Automate tasks such as shipment routing, carrier selection, and tracking shipments.
  • Optimize warehouse operations by predicting demand and allocating resources more efficiently.
  • Improve customer service by providing real-time shipment tracking information and responding quickly to customer inquiries.
  • Identify and mitigate risks by analyzing data from various sources, such as weather forecasts, traffic patterns, and historical shipment data.

In addition to improving processes, AI can also be used to reduce costs and for several other reasons:

  • Identify and thereby eliminate waste in the supply chain.
  • Negotiate better rates with carriers.
  • Improve fuel efficiency by optimizing route planning.
  • Better visibility of their supply chains.
  • Reduced costs.
  • Improved customer service.
  • Greater agility and responsiveness to change.

While AI is still a relatively new technology, it is already significantly impacting the 3PL industry. 3PLs that are early adopters of AI can gain a competitive advantage by using their existing data to improve operations, reduce costs, and provide better customer service.

How 3PLs Use AI To Leverage Existing Data

There are several ways in which 3PLs use AI to leverage existing data. Some of the most common use cases are:

  • Predictive analytics: AI can be used to predict demand, which can help 3PLs optimize their warehouse operations and avoid stock-outs.
  • Route optimization: AI can be used to optimize route planning, which can help 3PLs reduce fuel costs and improve delivery times.
  • Fraud detection: AI can detect fraudulent activity, such as shipment detours and cargo theft.
  • Customer segmentation: AI can segment customers based on their needs and preferences, which can help 3PLs offer a more personalized service.

Benefits of using AI for 3PLs

  • Improved efficiency and productivity
  • Reduced costs
  • Improved customer satisfaction
  • Increased agility and responsiveness to change

Challenges of using AI for 3PLs 

  • The cost of implementing and maintaining AI systems
  • The need for data scientists and other AI experts
  • The potential for bias in AI systems

The Future Of AI In The 3PL Industry

AI is a rapidly evolving technology that will likely have an even greater impact on the 3PL industry in the coming years. As AI systems become more sophisticated and affordable, more and more, 3PL companies will be able to adopt this technology and reap the benefits.

Inflation and labor shortages continue to burden business leaders in this space—no sign of these symptoms ending soon with current societal challenges. This is where companies such as Bar Code Depot can provide your 3PL with barcoding solutions that keep your warehouses running at maximum efficiency. 


3PLs that can utilize their existing data with the help of AI will be well-positioned in the coming years. AI can help 3PLs improve operations, reduce costs, and provide better customer service. 3PLs that are early adopters of AI can gain a competitive advantage and establish themselves as industry leaders. Ultimately, the contributions of AI to the supply chain, whether in warehousing, freight forwarding, or last-mile stages, enable businesses to improve the efficiency and reliability of their logistics operations.