AI itself has had a heyday in modern industry. One study found the use of AI in business processes has jumped 25 percent year-over-year as companies of all kinds integrate smarter computing processes to increase efficiency. The power of this tech across shipping and supply chains, in particular, is transforming the industry in the form of data analytics, connected monitoring systems, and automated processes. Understanding these tools and the extent of their impact on global trade requires a deeper dive into the power of AI in shipping logistics and how companies are already applying these automated solutions. Here, we’ll explore these topics and more.
The power of AI in shipping logistics
First, let’s more properly define what we mean by AI. Artificial intelligence covers a broad field of smart processes, all of which use algorithms and data in order to make a computer perform a task previously associated with human intelligence.
Obviously, this definition ranges far. From social media algorithms to autonomous vehicles, AI plays a role. But in the midst of all the capabilities of AI, one function is particularly powerful. Machine learning is a subset of AI that enables computers to make decisions based on data analysis. This process is fueled by big data, utilizing the insights possible through recorded information to process all kinds of patterns and predictions. As a result, a host of new devices that integrate machine learning are making life easier.
These devices and systems include things like the following:
- Smart home systems like Amazon’s Alexa
- Personalized advertising across the web
- Translation algorithms like Google Translate
- Autonomous vehicles
Because of the ability of machine learning to improve processes the more data it has, each of these systems and more are only going to get better. In terms of shipping logistics, the implications of AI-powered functions are widespread.
First, smart devices generate immense amounts of data regarding supply chains, inventory, warehouse processes, freight, routes, and more. This data is then made available to data analysts and AI software that intelligently assembles the information and connects important data points.
With such available insights, shipping logistics can be improved across the board. The benefits include:
- Reduced costs
- Faster transportation
- Seamless inventory tracking
- Reduced fossil fuel emissions
- Enhanced productivity
AI tech is driving all kinds of improvements at every level of the shipping logistics industry, from expense management to safety measures imposed. This means immeasurable benefits with the right applications and a cleaner future for the world. But how are shipping logistics professionals applying this tech now?
How logistics teams are already using AI
While there is definitely room for improvement in modern AI tools, this technology has advanced the sectors to which it is applied. In navigating shipping and freight solutions, AI allows for optimization never before possible. We see these benefits most clearly in the ways fleet managers are using AI to improve shipping as well as the strategic supply chain methods used throughout the pandemic.
AI in fleet management
In fleet management, AI delivers tools and insights capable of transforming industry efficiency. And these tools are already in use and available to businesses. Integrated Video, for example, applies artificial intelligence to fleet management through the quick and seamless analysis of driver footage. The AI scours video data, assembling insights that give fleet managers a better sense of their fleet and how it operates. In turn, these insights offer:
- Quick review of raw driving footage
- Improved driver behaviors
- Risk mitigation
- Liability protection
- Insurance discounts
AI in fleet management is all about information and awareness, two tools that drivers need in order to stay safe and reduce unnecessary risks, including fuel emissions. With AI, data can be harnessed to make better decisions throughout global trade.
AI in strategic supply chains
The needs of the global pandemic caused chaos throughout supply chains. Suddenly, shutdowns and outbreaks made it impossible to rely on a single source for materials, goods, and services. Companies have had to build strategic approaches to supply chain management on the fly, and AI has helped.
Nestlé is just one example of a company that has made effective use of AI to improve its methods of predicting demand and coordinating inventory, thus reducing its own levels of waste and overstock. Nestlé uses an AI system provided by software company SAS to apply statistical analytics to demand variables among their 10,000+ SKUs. As a result, they can better understand how promotions and deals will drive demand and necessary supply.
Such a real-time application of AI in supply chain navigation can be immensely useful in saving money and cutting down on waste. No doubt, the future of shipping logistics will be defined by the application of smart tech to fuel innovation and efficiency. But how far can we go?
The future of automated delivery systems
Shipping logistics is a field that requires as much information as possible to function properly. From inventory rates, weights, and locations to route management and coordination, there is plenty that goes into the field that AI and automation can streamline.
In the future, consumer-focused, personalized shipments will be made possible through the broad application of these tools. Whether this entails the use of drones delivering select products right to your door remains to be seen, however, it is certain that the level of personalization that has come to dominate marketing through AI and automation will come to shipping logistics. Already, we see evidence of this in Amazon’s ability to deliver many products within a day.
As AI improves, so too will the automated tools that power greater awareness and efficiency in shipping logistics. This means faster deliveries for the world and an easier system of global trade. Businesses making use of this tech now will undoubtedly have an edge on the competition as AI adoption becomes more widespread.
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