Experts predict that 2018 is going to be a big year for artificial intelligence, machine learning, and intelligent automation. In recent times, there has been an increasing awareness among most businesses in logistics on the competitive edge of these technologies.

As investment in AI technologies almost tripled in 2017, Gartner has predicted that AI is expected to be pervasive in almost every new software device by 2020.

The logistics industry, with a combined revenue of $8 trillion, is one that has the potential for a massive growth using AI integration. In 2017, the sector also witnessed a huge growth with the boom in web-enabled devices or internet of things (IoT).

Along with this, a digital marketing boost has led to an increased consumer growth for various e-commerce sites. Thus, the number of customers and their expectations need to be addressed and this is where automation comes in handy for logistics management.

Automation in logistics is also at a nascent stage. According to McKinsey Digital Reports (Logistics), implementing automation can deliver up to 30% increase in transaction speed, 25% reduction in cost, 100% accuracy and improved compliance.

Service providers across the globe have begun to observe an increasing need for actionable intelligence to make sense of big data and enable quick decision making. This is exactly where the unique capabilities of AI would come into prominence in a logistics organization. No wonder these service providers are spending millions on use of transformational AI and innovations to facilitate various cumbersome processes in the supply chain.

These technologies are now ready to make the supply chain management effortless and seamless. Businesses and customers can take full advantage of the speed, accuracy, ease of analysis, conception, supplied selection, implementation, and delivery of their logistics operations. All of these would lead to more revenue, reduction in operation costs and better customer service.

Logistics are crucial to the long-term productivity of an enterprise. DHL’s Logistics Trend Radar has predicted three major trends driving logistics innovation: self-driving and unmanned vehicle technology, the IoT and logistics driven by AI and machine learning. AI and machine learning are set to be a game changer for customer services that include third-party logistics, fourth-party logistics and in-house logistics.

Here are the key processes associated with the logistics industry that will benefit from a digital transformation:

Advanced warehouses: The growth in e-commerce will transform logistics delivery models. Various e-commerce businesses are increasingly using automation in their warehouse processing for sorting, recording, packaging, and invoicing with the optimal loading of freight containers for faster delivery.

The online freight services market will gain traction by implementing intelligent automation, and this adoption will also accelerate the warehousing segment as per various forecasts by industry leaders.

In-Transit Visibility: The logistics industry involves a complex set of systems where products are passed on from manufacturers to suppliers, distribution centers, retailers and finally to the customer. This increases the overall cost of doing business.

AI-powered technology can enhance in-transit visibility in a major way. There would be an increased use of cloud-based GPS and technology like Radio Frequency Identification (RFID) that would help track a product as it moves from point to point. This is useful is predicting the exact time of shipping and delivery. Use of real-time sensor data and environmental data allows for most precise predictions thereby raising overall productivity standards.

Location prediction and quickest delivery route: Unpredictable environment, fuel costs, traffic and labor costs hamper resources and productivity. Use of automation can ensure timely delivery through more efficient and accurate route performances. This is further enabled by better location and tracking of both deliveries and vehicles. The estimated time of arrival can be predicated and communicated to consumers in advance thus enabling quick corrective actions if needed.

AI is highly effective in leveraging data platforms, creating datasets to regulate anomalies and manage intricate dataset to perfection and creating a personalised experience using last mile delivery.

Using AI, Mediaan developed a model that predicts orders per delivery address which increased logistics planning accuracy by 80%.

Increased use of AI and ML in autonomous logistics: The union of AI and logistics would bring in a major boost to service providers, giving them the best competitive edge for enormous growth. As per expert projections, the shipping and logistics industry is slated to have a future that is completely digitized.

For several years, technology has comparatively penetrated less into the logistics sector. The trend has seen a shift in the last couple of years where the focus is now on the progressive use of machine learning, experimenting autonomous vehicles, self-driving trucks, and human-free ports. The use of AI technologies isn’t just going to be limited to these. Technology would be incorporated at many stages in the supply chain through the manufacturer, suppliers, the distribution center, retailer, and customer.

More intelligent decision making: Researchers are working on automation, ML, AI, Information and Communication Technology (ICT) applications to facilitate logistics services.

AI with a combination of machines can make intelligent decisions based on corrective data. The machines can learn and make corrective decisions with help of old data patterns. Intelligent automation can anticipate which customer requires their product delivered quickly and self-learning logistics system can detect patterns in data, issue accurate actions and even to a point recognise human handwriting.

With automation, manually copying data from internal systems back into any B2B portals, EDI, WMS can be eliminated along with, automating the scheduling thousands of appointments, enabling customer service reps to focus on higher value work, conduct ‘First Mile and Last Mile’ automation, F&A, and general reporting to name a few.

Natural Language Processing

NLP, both statistical and semantic, is another type of machine learning that is bringing a great change in the operational efficiency of supply chains. By 2021, NLP is projected to grow to $16 billion globally.

NLP systems monitor and learn through information exchanges via email, chats, texts, and voice when integrated with a Transport Management System (TMS).

NLP systems are constantly evolving and therefore ensure better accuracy in anticipating user-behavior, tracking status, weather conditions, traffic, and other factors by auto-populating shipping orders, bills, etc. saving a considerable amount of time and energy for the shipper.