By Jenna Bunnell, Senior Manager, Content Marketing, Dialpad

Artificial intelligence (AI) is one of the biggest business trends of the last few years. By 2030 the global AI market is forecasted to reach 1811.8 billion USD. Yep, that's billion with a ‘b'!

Logistics is just one sector that has been completely changed by AI.

Successful logistics operations are vital to good supply chain management, which can really give you the edge over a competitor. Without a steady stream of goods from manufacturer to customer, how can your business meet its goals?

Read on to find out the top five applications of artificial intelligence in logistics and how they can optimize your business operations!

What are the benefits of AI?

AI saves time and money by freeing up your employees to perform more complex high-value tasks. Robotic Process Automation (RPA) has already revolutionized business operations but AI can access information that RPA technology can't.

Where RPA supports human employees to do simple processes, AI can learn to do tasks on its own and constantly optimize that process from new data.

For example, having an auto phone attendant means that your trained receptionist doesn't waste time directing calls and can prioritize actually talking to customers.

Artificial intelligence relies on data. So any business task based around sorting or analyzing data can be optimized using AI. With the rise of big data and analytics, it's no wonder we're seeing AI accelerate too.

Logistics: from order to delivery

Logistics covers the flow and storage of goods within the supply chain. This includes inventory management, warehouse operations, distribution and transport.

Managing these operations requires many different companies and hundreds, or even thousands, of devices all communicating with each other!

A network this complex generates huge amounts of data. And as we've said, where there's data, there's room for AI applications.

 

Applications of artificial intelligence in logistics

AI has impacted almost every aspect of the supply chain. Let's take a look at the top five applications of artificial intelligence in logistics:

1.    Inventory management

Let's say it's Black Friday and your company has just received a thousand more orders than on a normal day. That's brilliant! Unless... you don't have the inventory to satisfy those extra orders.

Inventory management is about understanding how much stock you have, and when you need to order more. AI uses data to track the rate at which products are being shipped, and therefore when you'll run out.

Having separate data for each product means the AI can adjust inventory orders based on how quickly that specific product is selling.

2.    Predicting demand

Inventory management ensures that you have a steady supply. Economics 101 tells us that supply and demand are the foundation of business - unfortunately, demand is a lot harder to manage.

AI tools predict changes in demand by analyzing historical data and identifying trends. For example, Google Trends shows us that searches for ‘christmas gift ideas' start to increase in September and peak around December 10th.

 

Image sourced from trends.google.com

Data alone will tell you past trends. But integrating that data with artificial intelligence can make predictions to inform your company's current and future decision-making.

3.    Back-office automation

Back-office tasks can feel pretty repetitive, but that doesn't mean they don't require intelligence. AI is able to handle all types of data and digital paperwork that is too complex for basic automation.

These back-office tasks also include a lot of financial management. After an audit or report, AI might help the business decide how to address critical audit matters. The critical audit matters definition covers any pain points that need to be dealt with following an audit.

A well-trained AI tool can perform a much more thorough analysis of a logistics company's financial data than a team of human auditors. 

4.    Transport Management Systems

Finding the right transport solutions is time consuming. AI algorithms on shipping networks streamline this process by identifying carriers and businesses with matching availability.

Transport Management Systems (TMS) with AI support can also optimize routes to ensure deliveries happen on time. Machine learning accounts for factors like traffic congestion and customer preferences (many ecommerce businesses let customers choose their ideal delivery time) when planning routes. 

5.    Tracking deliveries

The biggest problem area in logistics is the ‘last mile', where goods are transported from the final warehouse to the customer.

The Internet of Things (IoT) describes physical objects, like delivery trucks, that exchange data through the internet via sensors or other software. AI benefits IoT by making the devices more efficient.

Real-time order tracking helps the company understand how efficient their delivery system is, but it also improves the customer's experience. In fact, 87.4% of customers said real-time order tracking made their buying experience more enjoyable.

 

Takeaways

AI can be applied to every stage of logistics, from order to warehouse to delivery. In this article we've explored how AI tools help process large datasets and make logistics operations more efficient.

As a reminder, here are just some of the applications of artificial intelligence in logistics:

• Managing inventory based on real-time orders
• Predicting customer behavior
• Automating back-office tasks
• Optimizing transport routes
• Tracking deliveries in real time
  

Try applying AI solutions to one of these areas in your business and see how they can help you streamline your operation.

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ABOUT THE AUTHOR

Jenna Bunnell - Senior Manager, Content Marketing, Dialpad

 

Jenna Bunnell is the Senior Manager for Content Marketing at Dialpad, an AI-incorporated cloud-hosted unified communications system that provides valuable call details for business owners and sales representatives with helpful guides like this Dialpad guide to enterprise collaboration. She is driven and passionate about communicating a brand's design sensibility and visualizing how content can be presented in creative and comprehensive ways. Jenna has also written for other domains such as Promo and Codemotion. Check out her LinkedIn profile.