AI IN FLEET MANAGEMENT
Unlocking Operational Insights from Fleet Data
Artificial Intelligence is not new. The term, which was coined in the 1950s, has long referred to machines performing tasks that would typically require human intelligence, but the rise of generative AI has changed the conversation. Since its public release in 2022, generative AI has been producing outputs that mimic human language and logic and is transforming business operations across all sectors.
While AI replicates human language and thinking, it is actually made up of sophisticated math algorithms that work best when fueled by enormous datasets. As a result, the trucking industry, which generates unprecedented volumes of data from vehicles, engines, telematics devices, routing software and more, is uniquely positioned to benefit from this surge in AI capabilities.
“We are getting more than 3,500 messages per second off of a vehicle,” said Tim Haynes, vice president of digital and customer data for Penske Transportation Solutions. “Right now, from our trucks at Penske, we are receiving more than 300 million messages a day.”
AI and advanced machine learning algorithms can process massive data sets to identify patterns and uncover correlations that human analysts would miss. It distills complex pieces of information quickly, enabling smarter and faster decisions.
“In fleet management, AI can take all of that data—those 3,500 messages per second—along with all of the variables and turn it into information that businesses can use to get detailed insights and make decisions,” Haynes said.
THE POWER OF AI IN FLEET OPERATIONS
Fleet management has always been fundamentally data-driven, and the role of information is becoming even more critical as fleets navigate an increasingly complex and uncertain operating environment.
“Fleets already have plenty of data. What they need is the ability to use it to enhance truck efficiency and get a comprehensive picture of their operations,” said Samantha Thompson, vice president of customer success and fleet telematics for Penske Transportation Solutions.
Historically, fleets have relied on static forecasts and standard industry metrics with little ability to create benchmarks that are exactly matched to their fleet. The challenge is that no two fleets are the same.
Fleets are inherently distinct, shaped by variables such as duty cycles, operating areas, vehicle specifications and the type of freight they haul. With AI, fleets can move beyond basic reporting to create customized performance benchmarks tailored specifically to their equipment, usage patterns and
operating environments. Instead of comparing themselves to a generic industry baseline, fleets can measure performance against a model built uniquely for them.
AI can also get incredibly granular, pinpointing the performance of specific assets or certain regions. The result is a new era of reporting that delivers more meaningful insights, useful performance comparisons and opportunities for improvement.
“Fleet managers need information to be presented in the most useful and user-friendly way possible.
AI is helping your management team to dig into the data, distill the information and identify the best strategies and paths forward,” Thompson said.
Thompson added that capturing data for the sake of data isn’t beneficial. “Fleets need the right insights to be available at the right time and are seeking out the key performance indicators that support their operational goals,” she said.
PRACTICAL AI APPLICATIONS IN FLEET MANAGEMENT
In a recent study by Deloitte, 99% of transportation executives surveyed said they expect AI to transform the industry. Several practical applications for AI in fleet management are already emerging. AI is reshaping how fleets operate, from identifying the most fuel-efficient assets to enabling predictive maintenance that reduces unplanned downtime.
VEHICLE PERFORMANCE
Fleet managers can use AI tools to sift through data and review the real-world performance of the fleet as a whole and individual trucks. They can also sort information to include certain tractors or a specific model year.
The data can identify the cost per mile for the fleet as a whole and at the individual asset level or operating area, which can uncover performance disparities, identify underperforming assets or operations, and determine which areas to optimize.
Knowing the cost per mile is also critical for setting rates.
Mining data can help fleets identify the best vehicle specs for their operating conditions and optimal replacement times, so they avoid keeping vehicles too long without replacing them too early.
FUEL EFFICIENCY
Even minor improvements in fuel economy can result in significant cost savings. AI can track fuel consumption and identify patterns or anomalies that indicate inefficiencies or potential issues. Analyzing driver, vehicle and hub-level trends to reveal key factors influencing fuel economy, such as driver behavior, poorly maintained vehicles or the wrong vehicle specs, can improve fuel management and drive cost savings.
“Are you getting preventive maintenance done on time and is it current? How old is the truck? What is the idle time? Do you have an aero package? What is my load factor? Thousands of variables contribute to fleet and vehicle performance, including miles per gallon,” Haynes said. “Different operating points and key components can be relevant at different times, so AI models are constantly flexing to analyze the most relevant information and provide useful feedback.”
Fleets can also use AI to compare their operations to like fleets. “Our customers want to know their utilization and my MPG not only for their vehicles but also across similar industries,” Thompson explained. “I’m running a Class 8 and getting 5.8 miles per gallon. Is that good or bad?”
Fleets can then use the knowledge to take corrective action, build future specs or determine which equipment to replace.
UTILIZATION
Vehicle utilization directly impacts profitability, operational efficiency and productivity. AI-powered utilization analysis enables fleets to reduce idle time, improve route planning and spread workloads evenly. “Utilization isn’t just about vehicle use and miles. It is also important to know how many hours it is being run and how it is being used,” Haynes said.
Drilling down into utilization metrics improves productivity and avoids premature wear on individual trucks while maximizing driver mileage. AI can also quantify empty miles, which represent lost revenue opportunities and higher operational costs due to unnecessary fuel usage and vehicle wear. Reducing empty miles through route optimization, improved dispatching or backhauls improves profitability and resource utilization.
Ultimately, enhancing fleet productivity through better vehicle utilization, allows carriers to lower the cost per mile and increase the revenue per trip.
BENCHMARKING
Benchmarking is a vital tool for companies to compare their performance and critical metrics to industry standards and similar operations to uncover opportunities for improvement and gain a competitive advantage. Several industry reports provide averages, but they limit fleets’ ability to create benchmarks that match their operations.
AI can allow fleet managers to measure key performance indicators and generate dynamic comparisons to similar operations and equipment. It can also automate the generation of reports on various fleet metrics, saving time and providing more accurate and timely information for decision-making.
PENSKE INTRODUCES MORE DYNAMIC BENCHMARKING WITH FANTASY FLEET
Tracking and comparing real-world operating information, such as utilization and MPG, at the vehicle level is critical. With AI, Penske is taking benchmarking one step further and enabling customers to create a data-driven “fantasy fleet.”
Similar to building the ideal team in fantasy football where each player’s real-world stats are analyzed to create the strongest possible lineup, Penske uses AI to identify vehicle-specific, real-world performance data to build a customer’s ideal fleet.
“You are looking for the best operators, the trucks with the highest MPG or utilization, and those assets that are performing well on an individual level. Then, analyze your operations to see what it would look like if you could build the ultimate team,” Haynes said.
The “fantasy fleet” can be used to inform spec’ing decisions and strategic investments that will improve efficiency and profitability across the fleet.
MAINTENANCE
One of AI’s most transformative uses is predictive maintenance. By analyzing fault codes and historical repair data, AI can forecast failures before they happen and trigger alerts or interventions, allowing fleets to maintain equipment proactively.
AI can not only alert managers to a problem but also identifies what’s causing it. By examining thousands of variables, it can uncover the root cause of an issue, increasing efficiency.
KEY CONSIDERATIONS WHEN DEPLOYING AI
AI is a powerful tool, but it requires a strong foundation to be effective. Without the right framework of data, validation and oversight, AI and ML solutions can drift, provide inaccurate results or compromise sensitive company information. “You need to have someone who is a domain expert actively involved, especially in the initial phases of the models, to provide feedback that allows the models to learn better,” Haynes said.
Drift in AI happens when a machine learning model’s performance worsens over time because the real-world data it sees starts to differ from the data it was trained on, making its predictions and analysis less accurate.
Fleets need to be intentional about how they source, validate and secure their data. “The quality and reliability of the data pool is critical,” Haynes said. “For the AI systems we’ve created at Penske, we have validated models against known industry standards and data points. It’s key that models are checked and rechecked. Within AI, any models can drift as data changes and get off center.”
Haynes compared trusted data points to universally accepted physical measurements. “We know 12 inches is a foot, three feet are a yard and there are 39.37 inches in a meter. These are the absolutes
and the knowns. The same principles apply to AI,” he explained. “There are situations where we know what a truck is going to do because it has been validated over time, and it has become the known we can measure against.”
Validating data sources and monitoring modeling is an ongoing process. “It takes constant, iterative feedback to enable confidence in the results,” Haynes added.
COMMON MISCONCEPTIONS ABOUT AI
Use of AI is increasing, but there is still a lot of confusion and even misconceptions about what it can and can’t do. One of the most important issues users need to be aware of is that generative AI isn’t actually intelligent, and it doesn’t know if it is correct. “ChatGPT is a great example. It’s following rules and giving you an answer, but it has no concept if it’s right or wrong,” Haynes said.
AI is not autonomous decision-making and it isn’t thinking or deciding like a human would.
“It doesn’t tell you what to do. It’s telling you what you could do,” Haynes said. “It is math that recognizes patterns. It can’t reason or recognize when something doesn’t make sense.”
Because of these limitations, human oversight remains critically important. “You have to have that common sense. Somebody has to be looking at it and saying, ‘yes, this makes sense, and yes, this is the action we should or shouldn’t be taking,” Haynes said.
“AI today isn’t the independent-thinking machine we imagined in 2001: A Space Odyssey, but it does allow us to take massive amounts of data and start turning it into information. It helps pull out the highlights and build models that let us focus on what really matters.”
– Tim Haynes, vice president of digital and customer data for Penske Transportation Solutions.
STRATEGIC ADOPTION OF AI SOLUTIONS
Data is a strategic asset that can improve all aspects of operations when put to use correctly. Given AI’s vast potential in fleet management, fleets that continue to rely solely on traditional tools and manual processes risk falling behind, missing an opportunity or making the wrong decisions. AI is increasingly becoming a strategic necessity to survive as the trucking industry becomes more competitive.
Fortunately, AI technologies are becoming more accessible to fleets of all sizes through vendors and service providers. “As a fleet, you don’t have to make this investment on your own. You can find the right partners,” Haynes said, adding that it is essential for business leaders to find solutions that provide value. “Don’t rely on a partner that only relays what the data is saying. Find someone who says, ‘this is what it is telling us and here is what you can do about it.”
Penske has harnessed the power of AI and ML through Catalyst AI™, a decision engine that analyzes hundreds of thousands of data sets, automatically identifying similar fleet operations, enabling a precise apples-to-apples comparison of critical operational variables. Within Catalyst AI, more than 300 models run simultaneously to deliver the insights and actions that help drive change.
“Fleets have invested a lot of money in their assets, and they need their trucks to be on the road, moving freight,” Thompson said. “Their needs haven’t changed, and with newer technology, we are able to help fleet managers do even more with their equipment.”
Contact Penske Customer Success at 844-426-4555 to take advantage of the latest tools to compare, analyze and optimize fleet operations.
i Dartmouth College. Artificial intelligence (AI) coined at Dartmouth. Dartmouth. Retrieved April 18, 2025, from https://home.dartmouth.edu/about/artificial-intelligence-ai-coined-dartmouth
ii Sweeney, M. (2023, November 30). Generative AI turns 1: A timeline of ChatGPT, OpenAI and more. CIO Dive. https://www.ciodive.com/news/generative-ai-one-year-chatgpt-openai-timeline/698110/
iii Deloitte Insights. (2024). Generative AI in transportation: Where could it deliver value? Deloitte. https:// www2.deloitte.com/content/dam/insights/articles/us187568_cic_gen-ai-in-transportation/Gen-AI-intransportation.pdf
