Artificial intelligence is not just another technological advance, it has revolutionized everyday life and is accelerating the evolution of all industries, and logistics is no exception. Its use is opening up a wide range of possibilities that represent, recurrently, drastic changes in the operation of logistics systems at all stages and phases of the chain.
Starting from the planning itself, by using AI hand in hand with big data, the companies are becoming more dynamic in deducing users' intent to consume certain products, that is, they now have the ability to anticipate the demand of their markets. In addition, today they are able to early adapt and operate logistics accordingly, to avoid both inventory understocks and overstocks, thus saving resources.
Consequently, the operation is becoming more affordable for supply chain managers and logistics specialists, which also can be directly translated into growth and competitive advantages for companies.
However, there are concrete AI applications that are making a difference in logistics.
For example:
- Automated warehouses
Warehouses are the heart of logistics, and their processes represent great challenges and opportunities. By using artificial intelligence, and empowering a management software with applied robotics, it is possible to automate operations such as product transport and placement, allocating only the necessary resources for each task.
There are even "smart warehouses" where artificial intelligence allows visualizing the object data. In fact, it is possible to practically automate all day-to-day operations of a warehouse.
A good example of that are the warehouses with online platforms, which use artificial intelligence to automate processes such as goods receipt and wrapping. With barcode-free object recognition, the products are sorted right after being unloaded from the containers. Quickly, while 3D wrapping is going on, products can be simultaneously measured by AI and computer vision, with no need for barcode scanning.
- Supply chain automation and visibility
In supply chains, many processes are susceptible to automation using AI, from real-time purchase order monitoring and inventory updates to issuance of supply orders; while goods traceability is improved. It should be mentioned that, generally speaking, investing in technology optimizes the supply chain.
- Transport coordination
Using AI, you can define optimal routes for deliveries, as well as recalculate and/or modify them in real time if necessary.
This allows visualizing and manage the ongoing transfers of merchandise, achieving a better warehouse management.
- Increased productivity
The use of algorithms and automated calculations result in better solutions to considerably increase the productivity in the warehouse, especially for online retailers. In addition, now there are AI-controlled robots that ensure a simultaneous and almost error-free communication, which also contributes in this regard.
- Accounting processing
AI is capable of handling essential business roles as much higher volumes, e.g., processing millions of invoices, from thousands of vendors, partners and suppliers, taking a huge burden off logistics accounting teams. In addition, AI technologies such as spoken language processing are capable of extract essential information, such as billing amounts, account information, dates, addresses and stakeholders, among the great number of invoices the company daily receives. Once the data is classified, an RPA (robotic process automation) bot can extract and enter them into the company software to generate a purchase order, make payments and send the customer an email confirmation, all of that with no human intervention. Some systems that use these technologies can even be used to detect invoice frauds.
Some benefits of integrating AI in the supply chain
Task automation
There are artificial vision systems capable of identifying errors or predicting needs, as well as alerting the human resources those need to be solved, thus streamlining the process of merchandise management. in the warehouses. In this regard, artificial intelligence can also be used to schedule or execute maintenance tasks at the warehouse and transport activities.
Demand organization
Knowing in advance what customers need is a crucial aspect when it comes to optimize the supply chain. This is achieved by knowing data collected by the company itself, but also insights on macroeconomic, statistical and consumer trends that address a better management of the supply chain. AI models include predictive components that allow us to tailor planning by considering different scenarios, both in the supply chain itself and in response to developments in world markets, such as changes in demand, price fluctuations, supplier changes, etc. This AI predictive nature allows planning ahead, i.e., the system learns from these changes and improves over time.
Solves logistics problems
AI throws up models with a more detailed description to solve logistics problems.When testing and simulating steps are added, its validation is closer to reality. For example, in transport, combining artificial intelligence with analytics and big data helps to reduce costs. This also contributes to providing relevant information that improve company's sustainability indicators. Helps in warehouse and inventory management If the SKUs are managed within the inventory, products can be located through AI in real time, to monitor sales, to know the inventory status, to predict needs in demand and to detect errors or scams in the supply chain.
Allows you to keep track of suppliers
Supplier delivery times directly affect the supply chain effectiveness and productivity. By using artificial intelligence and analytics, it is possible to quickly respond to these contingencies, and even anticipate them, providing a report on what could happen along the entire chain. An example of that is building digital twins, that can perform diagnostic and predictive tasks.
Solistica integrates AI in all its processes: in warehousing we use automated systems that save and manage space smartly, as well as reduce maneuvering time to the maximum; and in transport, we count on route optimization, risk management and fleet maintenance systems.
In summary, the contributions of AI to the supply chain, whether in the warehousing, freight forwarding or last mile stages, allow companies to make their logistics operations more efficient and reliable.
Used strategically, AI can reduce errors, minimize risks and repeated operations, while offering many applications that can quicken the logistics process and ultimately increase competitiveness. Its use will certainly continue to create a great impact on logistics processes in the near future.
