Trimble Insight 2024: Navigating the Rise of AI in Transportation and Logistics

The application of artificial intelligence (AI) and machine learning (ML) in logistics is no longer a futuristic idea. These technologies are already revolutionizing how companies manage operations, improve efficiency and scale their services and this is no less true in transportation and logistics. During a recent panel discussion at the 2024 Trimble Insight Tech Conference, several leading technology experts shared their perspectives on the challenges and opportunities for integrating AI and ML into transportation operations.

Article Highlights:

• • AI is starting to play an increasingly important role in automating broker activities that traditionally involve a lot of manual work, such as booking and communications.
  • While AI can help streamline some processes, the human element is still crucial to transportation operations, as the work is often too complex for the current generation of AI.
  • AI solutions have the ability to help transportation and logistics companies quickly scale their operations to meet growing customer demand.

AI for Fleet Management and Efficiency

One of the critical areas where AI is making a significant impact is in freight management. Anthony Sutardja, co-founder of Parade, explained how their capacity management platform helps freight brokerages optimize operations by using AI to drive automation.

The goal is to reduce the time it takes for brokers to find and book trucks, which traditionally involves numerous manual processes and communications. Parade’s platform pulls in data from mobile apps, load boards and visibility providers, enabling brokers to find trucks faster and automate booking processes. The platform leverages AI to cut down on time-consuming tasks, allowing brokers to focus on building strategic relationships with carriers.​

Oliver Jones, co-founder of Manifold, another freight tech company, discussed how their platform aggregates spot rates from various sources, giving brokers and carriers a centralized place to bid on spot rates. He pointed out that AI helps eliminate the problem of losing track of opportunities, as the system can capture and organize the data all in one place.

AI-Powered Conversations: Automating Communication

The transportation and logistics industry relies heavily on communication, presenting an opportunity for AI to take on routine conversations, such as brokers coordinating with carriers or operations teams scheduling deliveries. Technology like Parade’s Co-Driver automates interactions between brokers and carriers -- instead of brokers manually checking whether a load is still available or if a carrier is qualified, AI-powered systems can handle these transactional conversations virtually​.

AI doesn’t just automate routine conversations. As the experts mentioned, AI-powered systems can also handle cleaning up messy data, such as identifying different types of shipments and translating data from emails or other unstructured formats into structured and valuable insights.

By focusing on these simple use cases, AI can deliver repeatable and reliable results, reducing human error and freeing up team members to focus on more strategic tasks.

Balancing AI’s Potential with Human Expertise

One key takeaway from the panel was the emphasis on augmenting, but not replacing, the human work with AI. Chadd Olesen, CEO of AVRL, highlighted how AI in logistics is primarily used to augment workflows rather than eliminate human jobs.

For example, his technology connects a logistics company’s TMS to a shipper’s TMS, automating tasks like scheduling and back-office processes. The goal is to give employees more capacity and streamline their work, rather than reduce headcount​.

Charley Dehoney, co-founder of Upwell, added that AI can play a critical role in accounts receivable for logistics companies. Upwell’s system uses AI to automate the process of managing invoices and payments, reducing the time and effort needed to chase down unpaid invoices. Upwell’s platform integrates with both TMS and ERP systems to ensure invoices are correct and adhere to the shippers’ payment rules. With their solution, AI helps eliminate errors by automatically identifying and correcting issues like missing reference numbers or documentation, which can often delay payments​.

Cost, Efficiency and Speed: AI’s Financial Impact

One of the more compelling arguments for adopting AI in logistics is the financial savings it can offer. As discussed during the panel, AI-driven automation reduces the time spent on manual tasks and speeds up processes like invoicing, load booking and freight management.

Beyond time savings, the cost of implementing AI is becoming more accessible. Sutardja noted that AI-related costs have dropped dramatically over the past year, making it easier for companies to scale their use of technology without breaking the bank.

The use of AI also allows companies to deploy more personalized and scalable features. As Jones pointed out, development costs for AI solutions have also significantly decreased, allowing companies to create features tailored to specific customer needs. This level of customization wasn’t possible a few years ago, but the rapid evolution of AI technology now makes it easy for tech providers to develop and implement new features in a matter of weeks​.

Overcoming Challenges in Adopting and Trusting AI

Despite AI’s benefits, adopting new technology isn’t without its challenges. One of the key issues the panelists discussed was the difficulty of getting stakeholders on board with AI-driven change.

According to Olesen, it’s essential to have the right people in the room when discussing AI implementation -- this means including people from multiple departments, such as sales managers, operations directors and of course, the CEO, to ensure alignment across the company​.

Building trust in AI is another hurdle. In the logistics industry, where stability and reliability are of key importance, many businesses are hesitant to hand over critical operations to automated systems. To combat this, some companies take a phased approach to AI adoption. For example, instead of fully automating a complex process like appointment scheduling, businesses can start by automating smaller, less critical tasks, such as scheduling deliveries to specific retailers. This gradual approach helps build confidence in AI’s capabilities.

The Future of AI in Logistics

As AI technology continues to evolve, its role in logistics will only grow. Panelists agreed that the logistics industry is ripe for transformation, with AI offering solutions that not only reduce costs, but also enhance efficiency and scalability. AI is already transforming how businesses manage freight, communicate with carriers and process payments. However, for AI to reach its full potential in logistics, companies need to adopt a proactive and strategic approach to implementation​.

With AI-powered systems becoming more affordable and customizable, there has never been a better time for logistics companies to explore AI solutions. Whether it’s automating routine communications or managing complex workflows, AI offers the opportunity to streamline operations, reduce errors and ultimately improve the bottom line.

Visit the Trimble Insight 2024 event hub to read more. Or, contact our team to learn how Trimble can help your organization be as prepared as possible for any transportation industry challenges, contact our team.