Clark: AI is already driving your fleet—are you ready to catch up?
Forget the sci-fi hype: AI is here and reshaping fleet management right now. What used to be a novelty is now an operational necessity. Commercial transportation fleets already see AI’s transformative power across operations, finance, customer service, and logistics. If AI isn’t steering your fleet yet, it’s only a matter of time before it’s in the driver’s seat.
At a recent NationaLease gathering, TCI Leasing/Rentals’ Andy Figueroa and Cara Swank unpacked what fleet managers need to know to go all-in on AI. They discussed how AI tools like optical character recognition are already crunching through purchase orders and vendor invoices, while chatbots field customer questions faster than humanly possible. But here’s the challenge: How do fleets go from dipping a toe in AI to riding the full wave of potential? The key is preparation.
Preparing your fleet for AI: a new playbook
1. Know what you need before you shop for AI
AI can do just about anything, but not every AI solution is built for every fleet. Start by dissecting your operational challenges and goals. What slows you down? Where could data-driven insights overhaul your decision-making?
A fleet facing chronic vehicle downtime might prioritize predictive maintenance AI, while one focused on logistics might look to AI for routing and fuel optimization. Identifying your pain points narrows down the search for AI tools that’ll actually make an impact.
2. Create a bulletproof AI policy
AI is a tool, but without guidelines, it can turn into a rogue agent. A clear AI policy outlines how AI is used, who’s managing it, and the ethical framework around its deployment. Figueroa and Swank stress that a solid AI policy builds trust and transparency, calming nerves internally and showing clients that AI is there to enhance—not disrupt. A strong AI policy will:
- Define governance and accountability for AI projects.
- Tackle risks, like bias and data privacy, head-on.
- Ensure regulatory compliance.
- Set clear guidelines on employee interaction with AI.
- Foster trust within the organization and with clients.
3. Make sure your data is ready for action
Data fuels AI, plain and simple. But messy, siloed, or outdated data? That’s a one-way ticket to subpar results. Before you unleash AI on your fleet, get your data in order—break down silos, update records, and double-check for accuracy. Skipping this step makes every other step virtually useless. Without data prep, integrating AI is throwing cash into a black hole.
See also: How AI can reveal more about your fleet's fuel efficiency than raw mpg data
4. Think beyond departments—AI demands collaboration
AI can’t deliver in isolation. It needs input across departments—finance to track cost savings, IT to handle data, HR to address employee concerns. Cross-functional collaboration is what transforms an AI project from a tech experiment into a strategic win that aligns with the fleet’s bigger goals.
5. Test the waters with pilot projects
AI might be the future, but diving in headfirst isn’t the answer. Start small—test AI on a specific process like accounts payable using OCR for invoice processing. Pilot projects allow you to measure impact, make tweaks, and get the team comfortable with AI. Then, once you’ve ironed out the kinks, you can expand AI’s reach without breaking the bank.
Ready or not, AI is coming. Start prepping your fleet now and be ready tpreparedd the pack.
