Ford's Kevin Dunbar on Transforming Fleet Management with AI-Powered Intelligence

As businesses look for ways to improve fleet efficiency, reduce operating costs and simplify day-to-day operations, artificial intelligence is emerging as a valuable tool for turning vehicle data into actionable insights. Ford Pro AI was recently named AI-Powered SMB Solution of the Year by the 2026 AI Tech Ascension Awards. The platform is designed to help fleet managers access critical information faster, identify potential issues and make more informed decisions without navigating complex dashboards or reports.

We sat down with Kevin Dunbar, General Manager for Ford Pro Intelligence, to discuss how Ford Pro AI is addressing real-world fleet management challenges, the importance of accurate and reliable AI insights, and how intelligent technology can help businesses operate more efficiently.

Ford Pro AI was named AI-Powered SMB Solution of the Year. What problem did you set out to solve?

Kevin Dunbar: Fleet managers have plenty of data. What they often do not have is the time to sort through it.

They are managing vehicles, drivers, maintenance, costs and customer needs. We surveyed fleet managers, they told us they spend an average of 23 hours a week on administrative tasks across areas such as maintenance, dispatch, budgeting, human resources, and customer service. They estimate that AI could reduce the time they spend on those tasks by about 40% or more.

We designed Ford Pro AI to make their existing fleet data easier to access, enabling them to act quicker. A fleet manager can ask a question in plain language, get a clear answer based on their fleet’s distinct information, and be directed to the relevant area within Ford Pro Telematics Software to take the next step. The goal is simple: less time digging and more time running the business.

There are a lot of AI tools on the market. What is different about Ford Pro AI?

Kevin Dunbar: This is not a general-purpose chatbot that has been adapted for fleets. It was built specifically around the work fleet managers do every day.

Ford Pro AI combines Ford’s commercial vehicle experience and proprietary vehicle data with a multi-agent architecture built on clean, structured information from each customer’s own fleet. It’s a closed model that cross-checks responses against customer-specific data rather than using pooled fleet data, information from the internet, or generic industry benchmarks.

That matters because the questions are specific. A customer may need to know which vehicles require service, what is behind an engine fault, which vehicles are being underused, or where fuel and repair costs are increasing so they can act quickly to save on fuel costs. Ford Pro AI helps turn those questions into information the fleet manager can act on.

What does Ford Pro AI help fleet managers do today?

Kevin Dunbar: It helps them get answers faster across three areas: vehicle health, driver behavior, and reporting and costs. A fleet manager can ask which vehicles need service, whether vehicles were used outside operating hours, which vehicles recorded speeding or harsh-driving events, how much the fleet spent on fuel or repairs, or whether certain assets are being underused.

Ford Pro AI is  read-only. It does not take action on a customer’s behalf, but it can direct the customer to the relevant area of Ford Pro Telematics Software to review more information or complete the next step. That keeps the fleet manager in control.

Why is customer-specific data so important when applying AI to fleet operations?

Kevin Dunbar: Because fleet decisions have real operational and financial consequences. A generic answer is not enough when a vehicle may need service or a business is trying to understand why its costs are changing.

Ford Pro AI is built on data from the customer’s own fleet. Its multi-layered architecture uses multi-agent validation and clean, structured data models to reduce the potential for hallucinations and errors.

We also believe the customer has to remain part of the process. Ford Pro AI can surface information and point to a potential issue, but the fleet manager is responsible for reviewing that information and deciding what to do next.

Some people worry that AI will replace jobs. How do you think about the relationship between AI and fleet managers?

Kevin Dunbar: Fleet management is a hands-on job. It involves people, vehicles, customers, and situations that do not always fit neatly into a dashboard. AI can help with the data work. It can spot a trend, surface an issue or pull together information that might otherwise take time to find. But it cannot calm a driver after an accident, manage a customer issue, negotiate with a supplier or understand all the context behind a decision. Those parts of the job require experience and judgment.

We designed Ford Pro AI to extend what fleet managers can do, not replace them. If it can take some administrative burden off their plate, they can spend more time with their teams and  customers.

Why is now the right time to bring AI into fleet management?

Kevin Dunbar: Fleet vehicles are generating more information than ever. But more information doesn’t automatically make a fleet easier to manage. Fleet managers don’t need another dashboard to check. They need a clearer picture of what needs attention and what to do next.

AI can help close the gap between having information and knowing what to do with it. Instead of searching across screens or digging through reports, fleet managers can ask a question in plain language such as “Which vehicles need service this month?” or “Where can we reduce fuel use and costs?”

The value isn’t just getting an answer. It’s helping managers identify priorities and make informed decisions with less effort spent finding and interpreting the information.

Fleet operators bring the expertise. AI helps put the fleet’s information to work.

What do you see as the future of AI in fleet management?

Kevin Dunbar: The best technology should make the work simpler, not add another layer of complexity. AI should continue to focus on solving practical customer problems. Can we help fleet managers understand what needs attention? Can we give them clearer information to support decisions about uptime, safety, utilization and cost? Can we help them be more proactive and stay ahead of issues?

We are not interested in AI for AI’s sake. The measure of success is whether it helps give a customer their time back, keep vehicles moving, serve their customers, and run the business.