AI in Logistics: Transforming the Logistics Industry

Efficiency has always been a foundational value of the logistics industry. However, as global supply chains become more complex and customer expectations evolve, logistics companies are under immense pressure to keep up. 

That’s where tools powered by artificial intelligence (AI) come in. They have the potential to revolutionise the way businesses handle everything from inventory management to route planning. And they’ve already entered the fray.

Forward-thinking organisations are already making meaningful headway by strategically integrating AI into existing workflows and rethinking antiquated processes to be more data-driven. These early adopters have reduced logistics costs by 15% and improved service levels by 65%. 

With that in mind, here’s a closer look at how AI has set the stage for these major business improvements and plenty of others just like them.

 

Where AI Is Currently Used in Logistics

AI is already widely used in the logistics sector, with businesses deploying the technology to facilitate the following: 

 

ETA Prediction: Enhancing Delivery Accuracy

Predicting an item’s estimated time of arrival (ETA) has always been a challenge for logistics companies. The lack of accuracy in anticipating and meeting ETAs is a point of friction between businesses and their customers – who value convenience, cost and above all certainty.

AI is helping shed light on delivery processes, and it can even account for challenges like strikes, traffic, and weather conditions. Organisations can integrate AI into their delivery systems to provide real-time data about estimated arrival times. Businesses that use AI in their delivery processes can increase on-time delivery performance by up to 40%.

These systems gather information from multiple touchpoints throughout shipping operations, including carriers, warehouses, fulfillment centers, right down to store and (in Gophr’s case) individual courier levels.

 

Demand Prediction and Inventory Management

Inventory management and demand forecasting are critical for ensuring that products are available when and where they’re needed. 

AI excels in analysing buying patterns, and it has already proven to be an invaluable tool for reducing costs and saving time by optimising inventory management. 

For example, businesses are already using AI to facilitate ship-from-store options, and same day stock movements – an approach that reduces missed opportunities due to stockouts and allows businesses to meet customer demand consistently. 

 

Route Optimisation and Productivity Gains

Real-time route planning is a game-changer for logistics fleets.

By analysing various data points, AI ensures that routes are optimised at minimum daily and for the more advanced carriers, optimised in hour.

Researchers estimate that these analytics processes will boost logistics productivity by up to 40% by 2035 and result in far fewer failed deliveries. 

Carriers, in turn, can reduce vehicle wear and tear while slashing their fuel costs and promoting efficiency. Driving efficiencies that can be passed onto their end clients

This is where tech centric carriers have real opportunities – at Gophr we have over 50 data points on over 10 million same day deliveries (and counting), which is how we can build extra efficiencies into our routing.

 

AI in Workforce Planning and Staffing Predictions

It’s not the first application of AI in logistics, but it could be one of the most impactful on bottom lines. Despite developments in robotics, logistics is still a very labour dependent sector. So anything that can help manage labour resourcing and costs is incredibly valuable. 

Integrating AI in logistics workforce planning can ensure you have the optimum level of capacity to complete your deliveries and hit SLAs, avoiding under or overstaffing, thereby keeping your labor costs in check without burning out your team. 

Where AI really distinguishes itself is Day-Of Decision-Making: while long-term staffing forecasts are crucial, artificial intelligence also brings an advantage to impromptu decision-making in logistics. For example, AI can make quick adjustments to staffing levels and resource allocation based on current demands, unforeseen disruptions, or weather conditions.

By adapting to operational changes using AI-optimised recovery and execution plans, some logistics companies have seen a 15% reduction in driver travel time.

 

Training and Compliance

Artificial intelligence can also play a significant role in training and compliance, extending beyond simple monitoring. 

For example, with AI-powered image recognition, proof-of-delivery photos can be analysed in real-time to confirm whether packages are placed in the requested location, helping to boost customer satisfaction while reducing misdelivery complaints.

AI can also provide instant feedback to drivers who make procedural missteps or fail to drive safely, helping fleet managers maintain better oversight.

 

AI in Customer Service: Generative AI and Chatbots

Generative AI is making waves in customer service. Chatbots are becoming increasingly sophisticated and can tackle a wide range of basic customer service tasks. 

They can answer up to 80% of routine questions and handle those inquiries up to 80% faster than human agents. 

For us, the sweet spot is AI assisted vs AI replaced – so we’ll always have customer services reps available, simply because same day deliveries are always urgent and often requires a lot more communication to resolve. Plus they’re very rarely routine, especially when you’re working in specialised industries like pharmacy legal or pro-trade

 

AI for Back Office and Procurement Optimisation

Here’s a look at how AI can influence your back office and procurement efforts as well as other core administrative processes: 

 

AI in Procurement and Spend Management

Autonomous procurement systems are quickly becoming the norm, helping companies make data-driven decisions that boost their profitability. 

Machine learning algorithms can analyse past data to predict the best time to buy, helping companies negotiate better deals with suppliers. 

For example, Walmart uses AI chatbots to negotiate with equipment suppliers, which helps drive down costs and improve efficiency. 

 

AI for Financial Processes

Financial reconciliation can be a time-consuming and error-prone process. But AI is streamlining things by automating invoice matching and payments. 

By reducing manual input, AI decreases the likelihood of errors and speeds up financial processes across the board. 

Take Scarbrough Global, for instance. The company uses AI to automate invoice reconciliation, resulting in significant time savings and resources directed toward more strategic tasks. 

 

Emerging AI Applications in Logistics

Businesses are continuously exploring new and exciting ways to work AI into their logistics workflows. Here are a few applications that are currently breaking into the mainstream: 

 

AI in Delivery Updates and Milestone Visibility

Customers are eager to receive their orders and expect you to keep them in the loop with frequent delivery updates. 80% of consumers want delivery updates, if you don’t provide them, you’re adding friction to the customer journey. 

AI can automate these processes and minimise the risk of human error, ensuring your customers stay informed from order to delivery. It can also provide milestone visibility, allowing customers to track their shipment as it progresses through each link in the supply chain. 

Raft, a logistics company, is already making use of AI to enhance its transparency regarding shipments. It extracts information from emails and updates the brand’s delivery systems. The entire process occurs automatically, reducing the need for manual data entry. 

 

AI for Fulfillment Optimisation

AI can also accelerate your fulfillment processes by analysing stock locations and identifying the ideal place to source products based on proximity to the customer. 

Levi Strauss, the famous denim brand, recently launched Business Optimisation of Shipping and Transport (BOOST), a patent-pending solution that will integrate retail stores into customer-facing product searches. 

If an item isn’t available at a distribution center, BOOST will determine whether it is in stock at any retailer, giving consumers an additional option to order the items they want.  

 

Where AI Could Be Used in the Future

Here are a few ways you could deploy AI in the future: 

 

AI-Driven Autonomous Logistics Networks

Imagine a logistics network that is always getting better. AI could autonomously reallocate work and minimise emissions. 

Autonomous networks can also open the door for delivery localisation, meaning each fulfillment workflow would be customised based on where someone is. 

 

Generative AI in Supply Chain Management

Generative AI has the potential to replace traditional dashboards with interactive assistants that you and your team can query in natural language. 

You could type or say things like “Which inbound shipments are delayed?” and receive dynamic, data-driven answers. 

 

Potential Challenges and Watchouts

Despite its many upsides, you may encounter a few hurdles when integrating AI into your workflows. These involve the following factors: 

 

Data Privacy and Security

AI systems require an abundance of high-quality data. Collecting and storing all of that information can create new privacy and security concerns. Today’s consumers are more privacy-conscious than ever, with 80% concerned about protecting their data. 

You must ensure that you are ethically sourcing data and doing your best to keep it out of the wrong hands. Otherwise, you could face severe penalties under frameworks like the General Data Protection Regulation. 

 

Ethical Considerations and AI Oversight

AI is not infallible, and it requires human oversight to avoid incorrect decisions or bias. 

Additionally, you must ensure that you are using the technology ethically and equitably, especially when leveraging it for workforce management purposes. 

 

Algorithmic Decision-Making and Ethical Concerns 

This means that before relying on an algorithm to make business decisions, it’s vital to consider its ethical implications. 

 

There’s always a potential for bias in AI algorithms, so you must make sure they don’t inadvertently favour or penalise workers unjustly. By proactively addressing these concerns, you can ensure that AI is not only efficient but fair. 

 

AI’s Dependence on Data Quality

Poor data quality can lead to inaccurate predictions and decisions. You must prioritise high-quality, real-time data inputs to ensure that your systems are functioning optimally. 

 

Best Practices for Implementing AI in Logistics 

Here are a few strategies to help you effectively integrate AI into your logistics processes: 

 

Identifying and Addressing Specific Pain Points

Start by identifying why you want to use AI in the first place. Investments in AI tech can be costly, especially if you make these decisions without a clear purpose. You must tailor your AI solutions to specific needs that will make an immediate impact on your business. 

Let’s say, for instance, that your organisation is committed to making its supply chain greener. AI can help you identify the root cause of things like excessive fuel consumption and other operational inefficiencies. 

Once you’ve applied it to uncover these issues, you can implement targeted changes to make your business more efficient.

AI-powered tools can also play a key role in solving challenges once you’ve identified them. For example, you could use them to optimise routes, which could help address the fuel waste issue. 

 

Integration With Existing Systems

AI tools don’t perform well in a vacuum. They are most impactful when integrated with your other business software and systems. 

A fully integrated technology ecosystem that places AI at the center will help your business become more nimble and data-driven. 

With that in mind, it’s vital to map your data before implementing AI tools. Identify where you store critical business information and which systems are most important to your day-to-day processes. 

Clean up your data before integrating any systems with AI so you can maximise the benefits of your new technology tools. 

 

Get More Advice on AI in Logistics 

With the right partners in your corner, you can unleash the power of AI and accelerate your company’s growth trajectory like never before.

Learn more about how AI can fit into your logistics processes, schedule a consultation with logistics industry experts, and align yourself with forward-thinking solution providers like Gophr.