While your core function as a logistics provider is to move goods, you also require a vast array of resources to operate efficiently: transportation equipment, warehousing space, packaging materials, fuel, technology, and software, to name a few.
This article is part of our complete guide to AI in trucking.
Many logistics providers maintain dedicated procurement managers to acquire these resources at competitive prices and ensure timely delivery. These employees handle tasks such as:
- Supplier management: Identifying, evaluating, and selecting suppliers.
- Contract negotiation: Negotiating favorable terms and conditions.
- Purchasing: Placing orders and managing the procurement process.
- Cost reduction: Finding ways to lower procurement costs.
The good news is that Trucking Generative AI (GenAI) can assist with all of them.
Already, the public can ask free GenAI tools such as Chat GPT or Gemini questions like, “What shall I cook for my vegan dinner guests?” or even, “How can I optimize last-mile delivery for urban areas?” The more specific the prompt, the size, quality, and context of the training data, and the frequency with which these algorithms are updated and fine-tuned, the more accurate the responses.
Text-based GenAI, or large language models (LLMs), show great promise for logistics teams looking to simplify their procurement processes. LLMs can read emails and quotes, write responses, and analyze historical data to support logistics teams in their price negotiations.
Gartner predicts that by 2026, mainstream GenAI adoption in logistics will begin. Let’s take a closer look at where you can get ahead and take advantage of the technology.
Automated Quotation with Trucking Generative AI
Logistics planners receive tons of emails daily with discrepancies, additional orders, and unique package types. Historically this has been too fiddly for a machine to handle, but new technology, such as CH Robinson’s quote automation tool, reads emails and supplies quotes in an average of 2 minutes and 13 seconds.
Trucking Generative AI takes huge amounts of data, such as past shipments, fuel costs, and carrier rates, and instantly finds patterns to understand what affects prices. So, when a new shipping request comes in, GenAI can quickly assess the details (like weight, distance, and delivery date) and compare them to what it learned from its training data. This vast comprehension and speedy analysis helps it give a fast and accurate quote.
AI systems, telematics, TMS/ERPs, and other integrated tools can help gather relevant information to train GenAI tools. Then, either with the support of data cleansing tools or data engineers, the raw data is cleaned and formatted to create an accurate and consistent knowledge base.
Already, these LLMs can respond to up to 2,000 customer quote requests per day, which paves the way for automating other email-based processes between shippers, carriers, and customers. GenAI can support teams with repetitive tasks such as sharing proof of delivery documents, processing payments, or negotiating rates with carriers based on current pricing packages.wins could simulate different driving conditions, helping maintenance teams identify potential mechanical issues. It does this by looking at your maintenance records, engine data, road terrain, and truck model. Logistics teams can then simulate different outcomes based on truck speed and driver behavior.
It could also help support logistics planners with route planning and driver preparation. By simulating the impacts of driver behavior on the routes available, scenario planning tools can help teams select the lowest-risk route or train drivers to adjust their driving style based on road conditions.
Contract Management
In the same way, Generative AI for Trucking can extract data from emails, it can also look at existing contracts and create standardized templates for common contract types. You might use it to build specific carrier agreements or warehousing contracts, for example.
When fine-tuned to do so, the technology can recognize recurring terms and identify common clauses, while maintaining a uniform language and structure across contracts. This streamlines contract creation and time spent on drafting and helps mitigate risks associated with inconsistent or outdated contract language.
GenAI has accelerated data analysis, supplier interactions, and contract management — reducing procurement process times by up to 60% for The Oxford College of Procurement and Supply.
Back Office Automation
So we already know GenAI can pull relevant information from various data sources and convert it into structured data. But imagine all the back office tasks this impacts.
From invoice generation to report creation to both standardized and conversational communications, GenAI can support a wide range of repetitive and mundane tasks. Finance teams can streamline customer billing processes, and use sentiment analysis integrations to improve dispute resolution. Logistics planners can ask GenAI to help them reveal intricate relationships and patterns that conventional forecasting methods frequently miss, and distributors can make informed decisions regarding inventory placement and transportation routes, leading to streamlined operations and reduced expenses.
Who knows, maybe in the near future, industry professionals will use GenAI-powered chatbots to interact directly with their tools and ask them the following questions: “Which load was the most profitable last week?” “Which drivers are performing better than the average across my company?” or “Which locations should I prioritize in my planning soon?” Then, it will completely change how people work with the systems, and it will allow us to extract the insights in a much more efficient way. In the meantime, GenAI and LLMs are making huge strides in downsizing the administrative burden on logistics teams. By automating repetitive tasks, analyzing vast datasets at record speed, and flagging unusual patterns, logistics planners can upgrade their decision-making processes. And the best part is that you can converse with these tools in human language.
FleetMetrics applies this to the quote itself: it reads incoming requests, extracts lane, weight and dates, and prices each one against your costs, current capacity and market rates. The agent approves or adjusts rather than researching from scratch.
