Globally, supply chain trends have undergone significant revolutions. This is due to modern technologies such as AI, data analysis, and automation systems. All these innovations have significantly changed supply chain management. They have enhanced operations to be transparent, efficient, and responsive.
Due to rapid solutions and real-time visibility, AI in particular has been adapted to numerous problems in the supply chain industry. This, in great part, is due to AI’s capabilities to achieve better traceability, improved decision-making, and high customer satisfaction. In the clinical management of patient inventory, from demand planning to robotic automation, AI is preparing a brighter, more adaptive, and flexible overall supply chain management for disruptions.
Now more than ever, it is imperative for organizations to incorporate AI and technology trends in supply chain management.
That is why we wrote this essay, where we highlight new supply chain visibility trends in AI and other technologies. You can also learn their effects and potential ways to maximize organizations' development.
How Can AI Help Optimize Supply Chain?
Artificial Intelligence (AI) plays an important role in supply chains by offering various means to enhance efficiency, productivity, and dynamic chain control in operations. In particular, AI systems are engineered to process vast data in real-time, helping businesses avoid risks or maintain efficient processes.
5 Benefits of AI in Supply Chain Management
There are a great number of ways in which supply chain technology can be improved by integrating artificial intelligence. We at Desteia, for instance, leverage AI to find relevant information in communication channels between users and extract crucial data points needed for operators to perform their daily activities. But there are many other uses fir the technology which include, but are not limited to:
1. Demand Forecasting
By using AI, companies can make educated guesses of demand patterns by looking at historical information and trends. Because of this accuracy, businesses can avoid overstocking, stockouts, and overall misallocation of resources, hence providing consumers with what they need.
2. Data-Driven Decision-Making
The use of AI is especially helpful to businesses by analysing large amounts of data and delivering easily understandable insights. These, in turn, allow operators to make educated decisions. Not to mention that AI can use real time information, giving sound advice on how a company can adjust and respond to market shifts, competition, and customer demands, all for strategic development.
3. Time Data Access
The implementation of AI technology in warehouses could help organize large amounts of real-time information on inventory, shipments, and process efficiency—not to mention the capability of linking these data points to one another. This measure also enables businesses to respond quickly to delays, adapt their operations, and ensure the free movement of the supply chain during pressures.
4. Inventory Management
Implementing AI allows companies to maintain the right stock by observing the supply and demand volatilities of hundreds of SKUs at a time from a plethora of sources—a task that would take humans countless hours to do per SKU. This, in turn, could avoid overstock, which lowers holding costs and also guarantees the availability of goods based on demand, hence improving operative productivity and value.
5. Improved Safety
AI-driven technologies could be implemented to analyze video footage and other sources of life information. Such programs could, in turn, observe workplace conditions and alert if there is any danger or transgression of rules. These technologies safeguard employees and property and guarantee adherence to security measures to avoid loss through accidents.
In sum, supply chain risks can be effectively managed through these and other advantages provided by technology, resulting in enhanced efficiency, cost reduction, and flexibility in business operations. That is, all the needed steps to achieve supply chain resilience—an essential goal for enterprises wishing to enhance their operations.
6 Supply Chain AI Trends Transforming the Industry
Technology is evolving rapidly, and so are the opportunities for supply chain companies to take advantage of such tools. While there are many new uses of AI—and these are added every day—below we include some AI trends are at the forefront of supply chain transformation:
1. Generative AI in Logistics and Operations
In general, we should note that logistics is one of the fields where generative AI is currently being implemented. This includes automating activities such as improving routes, scheduling shipments, and communicating with customers. To do so, users apply machine learning to huge datasets to find insights and improve their decision-making through improved data analysis. Generative AI also enhances customer experiences with the help of more efficient chatbots that can answer more questions.
2. Low Code Data-Driven Platforms
Supply chain managers are now enabled through low-code platforms to create unique applications without more profound coding skills. These applications make data consideration and consolidation easier and allow tracking of shipments, inventory, and logistics. All this in a sector that is known to be reluctant to technology in the first place, thus reducing the barrier of entry for innovation.
3. Automated Warehouses
AI and robotic technologies are increasingly being adopted to integrate automated warehouses for storage and retrieval. These solutions save space, minimize the role of employees, and increase the order-picking rate.
4. Robotic Process Automation (RPA)
Standalone Robotics and Process Automation (RPA) encompasses repetitive work such as inputting, payments and invoices, and regulatory compliance checks. RPA can improve productivity and decrease expenses by removing human mistakes. This is also possible by increasing the speed at which processes are executed—just think how long it takes a logistics operator to send emails to a customs broker or to sort through documents. Some of the common uses of RPA in supply chain management is in order processing and inventory updating.
5. Internet of Things (IoT)
Internet of Things—ie, connecting devices online to receive real time data—allows for the tracking of consignments at every stage of the supply chain. Some shipments have sensors for the product's condition, location, and temperature to deliver it as required by the customer. Thus, IoT technology helps address supply chain transparency issues, minimizes losses, and increases customer confidence.
6. Predictive Analytics
Artificial intelligence applications also include predictive analysis. This helps to forecast disruption, supply chain management, distribution routes, and inventory management. Through the application of historical data and analysis of the current markets, businesses facilitate the use of predictive analytics. This will enable the right actions to be taken and some risks to be prevented.
What Is the Future of AI in the Supply Chain?
Since AI is such a recent phenomena, it is still unclear how it will look like in the future—let alone for the specific case of supply chains. In general, its application is likely to increase automation, improve analytical capability, and build a better integration of applications. More specifically, in the coming years, we can expect:
1. Increased Use of Autonomous Vehicles
Drones with AI capabilities to detect their surroundings and self-driving delivery trucks will transform last-mile delivery.
2. Better Predictive Maintenance
AI will reduce maintenance expenses and downtime by anticipating equipment breakdowns before they happen and enabling operators to react in real time.
3. Accelerated Sustainability Initiatives
By implementing AI, companies will be able streamline industrial procedures and compare hundreds of logistics routes to find those that lessen carbon emissions and encourage environmentally beneficial behavior.
4. Advanced Techniques for Collaboration
Platforms powered by AI will give manufacturers, distributors, and suppliers a base of information that they can use to work together. AI systems have the potential of connecting disparate data sources and communication platforms to create a common ground for development.
Leaders in the sector, such as Desteia, consider AI to be key to building a supply chain ecosystem that is more robust and sustainable. Businesses can preserve a competitive edge and future-proof their supply chains by staying ahead of these changes.
Transform Your Smart Supply Chain
AI implementation in supply chains has yielded significant advantages to companies. It is an efficient and affordable solution that increases customer satisfaction. Today, companies such as Desteia are taking a new approach to helping businesses manage supply chains.
For instance, with Desteia, companies can easily integrate data and achieve actual-time visibility on operations. Likewise, IoT devices and predictive supply chain analytics are making operations wiser, swiffer, and more robust.
Top logistics organizations have applied predictive analytics to the problem of delivery failures, decreasing them by 20 percent during the holiday season. This improved the company's routes, cut costs, and deepened customer value.
Thus, AI will continue to be a key enabler of supply chain advancements throughout the future of supply chain technology trends. If you are interested in discovering how our product can help your company enter a new era of efficiency, make sure to schedule a call!