The Past, Present and Future of AI in Transportation and Logistics

As AI and related technologies continue to mature and more AI success stories in T&L emerge, decision makers are quickly running out of excuses not to explore these solutions.

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Artificial intelligence seems to be popping up in every complex business these days. For example, property insurers are using AI to quickly analyze huge data sets of aerial photographs following wildfires to pinpoint damage to their policyholders’ homes – and kick off the claims process even before customers contact them. Banks are utilizing AI to scrutinize billions of credit card transactions and stop fraud based on its knowledge of where customers might logically shop – and where they won’t.

With these types of solutions being implemented successfully across so many industries, one has to wonder why the transportation and logistics (T&L) sector is so far behind. According to a recent survey conducted by YouGov for HERE Technologies, a developer of location data and technology solutions, of more than 900 T&L professionals in the U.S., U.K. and Germany, only 25% say their companies leverages AI capabilities.

There are many reasons for this, ranging from perceived cost to a continued focus on core systems such as ERP software. But as AI and related technologies continue to mature and more AI success stories in T&L emerge, decision makers are quickly running out of excuses not to explore these solutions.

How We Got Here

Ironically, this industry has a long history of effectively implementing cutting-edge technology. Rewind the clock roughly 10 years and recall when ocean-shipping companies ramped up their use of digital products including web portals and the use of application programming interfaces, or API’s. Freight forwarders and BCO’s were now able to retrieve dynamic data such as spot quotes and tracking information. The use of portals and API’s made the data more accessible for the customer, which in turn created a faster way to do business.

Of course, the digitization revolution is still going strong today, with T&L leaders continually innovating new solutions. Companies are even using API technology to measure their total carbon-dioxide output across their global value chain to gauge their progress toward net-zero emissions.

What's Next with AI?

So, in a similar vein, the industry needs to push forward with AI to realize the gains it promises, including greater efficiency, accuracy, improved customer and partner satisfaction and many others. Perhaps one of the reasons utilization is relatively low in T&L is because of the high levels of confusion and hype surrounding AI.

So, it might be helpful to break down AI technology into two real-world scenarios where these solutions are producing measurable benefits by eliminating some of the heavily manual processes that are inherent in T&L.

Back-office Document Management

It’s fair to say the T&L industry has been built atop a mountain of paper. Each shipment generates multiple documents that traditionally have required shippers to receive them from multiple points, collect them and manually rekey them into ERP or TMS systems. These include everything from bills of lading and customs documents to delivery orders. This process is slow, tedious and prone to errors.

Of course, optical character recognition (OCR) technology has been around for years. But OCR simply transfers text as it was written into a given system, with any errors included. However, if AI and machine learning (ML) are applied to this challenge, reams of paper documents can be digitized and input into core software without the need for rekeying – and with enhanced precision. AI/ML can be programmed to “cleanse” data by spotting problems like omitted values or duplicate entries. It also can learn to apply logistics terminology logic based on context using a large language model, a system that can comprehend and create everyday language (a concept known as natural language processing or NLP) by analyzing huge volumes of text.

If the AI doesn’t have the necessary information to correct an error, it will flag it for a human to intervene. This concept of “managing exceptions” is key because it frees people to spend less time on double-checking documents and more time on value-added tasks.

Moreover, AI can help improve workflows by seamlessly connecting all documents with their corresponding shipments to make it easy to track status. AI can simultaneously separate each document and categorize it by type (or whatever variables the business chooses) for immediate access.

Customer Service and Response

Another key area where AI can enhance operations and boost the bottom line is customer service and response. The typical T&L company is deluged with customer emails on a regular basis. In a typical large organization, dozens of humans are required to spend time answering these emails, logging into multiple portals, rekeying data and messages customers. This is valuable time they could be investing in proactive customer service and revenue-producing work.

The reality is that many T&L firms cannot keep up with the flood of inbound requests. According to a 2022 study where Rippey posed as a real importer/exporter to request quotes from 86 freight forwarders, only 31% responded and, when they did, they took an average of 50 hours.

Fortunately, technology can provide a fix for this issue. Third-party response automation tools are available that can answer incoming requests in seconds without human intervention. These solutions combine AI, ML, NLP and robotics process automation that can answer most logistics enquiries.

These tools (sometimes referred to as bots) can quickly analyze the content of a customer request received via email or chat, migrate data from the T&L company’s TSM or ERP systems, and then draft and send a personalized response. At the same time, the bot can trigger the correct workflow to update the firm’s systems (e.g., create a record for a new-business prospect in the CRM software).

Experience has shown that technology like this can successfully reply to approximately 70% of the most popular customer requests — including spot quotes, track and trace, sailing schedules and general service requests — in roughly 30 seconds.

Final Thoughts

AI has successfully moved out of the hype phase and into an era where it can provide sustainable, quantifiable, real-world benefits to T&L companies. For these organizations that are constantly looking for ways to drive efficiency while improving accuracy and responsiveness, AI-powered tools show great promise.

By automating repetitive tasks like document processing and routine customer responses, companies can liberate employees to concentrate on value-added tasks that truly support the overall business strategy. AI also can help enable long-term growth by giving organizations the ability to quickly scale workflows and, ultimately, increase the quote-to-booking ration with adding more staff. 

Just like digital portals and APIs revolutionized the industry in the recent past, AI has the potential to accelerate technology transformation in T&L and move forward-thinking companies into a more successful future.