AI in Fleet Management (Video): 7 Smart Takeaways from Our Panel of Experts
If you manage equipment today, you already manage data — on a computer or maybe still in paper logs. Location. Utilization. PM schedules. Fuel burn. Security. Work orders. The problem is not data. The problem is time, organization, decision-making and maybe converting records from physical to digital formats. That was the theme of Construction Equipment’s recent live Conexpo panel on AI in fleet management. We brought together three incredibly smart voices in the off-highway construction equipment space with expertise in fleet management, telematics, and machine building to discuss how data can be processed and used more efficiently with the help of artificial intelligence.
The panel featured Craig Gramlich, owner of Lonewolf Consulting, Jose Cueva, cofounder and chief product officer at Tenna, and Brent Steffen, vice president of Cat Digital Product Management at Caterpillar. I moderated. Like everyone else, we discussed AI, but we took it from a practical angle — what’s out there now and what processes do fleet masters need to put into place to utilize this technology in the near future. We filmed the whole discussion, and you can enjoy that video above. Below, I extracted seven key quotes that embody our conversation. Which direction will you go?
AI should process data into decisions
“If there was one headache that you could solve with AI and fleet management, what would it be? Data processing for decisions.” — Craig Gramlich
AI must fit real contractor workflows
“I think it’s making sure that the AI solution is practical and that it fits into their workflows.” — Jose Cueva
Good data comes before good AI
“When it comes to AI on the cloud, there’s tons of applications across all sorts of business processes that contractors have to use. But what the real key there is having good data that you can work off of. Without good data, really the AI outputs are not going to be useful.” — Jose Cueva
Fleets need signal, not noise
“That’s one of the biggest challenges our customers share with us. Help me separate out the signal from the noise. And that’s where we focus a lot of our analytics and data science on. Then serving up only the certain pieces of equipment that really need review inside of VisionLink.” — Brent Steffen
Predictive maintenance starts with PM discipline
“Before you get into predictive maintenance, really nailing your planned maintenance and executing your PMs on time is… the old adage is an ounce of prevention is worth more than a pound of cure.” — Brent Steffen
Mixed fleets are the real challenge
“A lot of the barriers for an end-user and a contractor is going to be their mixed fleet as it sits today. Jose talked a little bit about it… retrofitting the old equipment up to the same kind of standard that the new equipment comes naturally equipped with.” — Craig Gramlich
AI will reward momentum
“I would encourage every customer to lean in to using it because AI will reward momentum and acting quickly and learning how to use it.” — Brent Steffen
About the Author
Keith Gribbins
Keith Gribbins is the head of content at Construction Equipment, where he leads editorial strategy across print, digital, video, and social channels. An award-winning journalist with more than 20 years of experience, Keith has won 17 national and regional editorial awards and is known for his hands-on reporting style, regularly visiting manufacturers, operating equipment, and covering major industry events worldwide.