The impact of generative AI on fleet management

Artificial intelligence (AI) is rapidly transforming fleet management, bringing new efficiencies to time-intensive tasks and cost management challenges.

Fleet managers have been using AI to understand and produce content, like summarizing complex documents, refining executive reports or developing training materials. ¹  

But as generative AI evolves and its footprint within fleet management grows, the possibility of more advanced, accurate and easier-to-understand insights expands.  Just over 30% of fleet managers plan to implement generative AI within a year, and more than half are looking toward AI-powered interfaces for more powerful data analysis. ²  

To stay competitive, managers should understand where AI fleet management can deliver value now and what new capabilities are just around the corner.  

Emerging uses cases of AI fleet management 

Fleet professionals have more operational data at their fingertips than ever before, covering everything from driver behaviors to vehicle performance. But that level of visibility is a double-edged sword and most fleet managers experience information overload.

While the data holds valuable insights that can help fleets prioritize safety, boost efficiency and reduce costs, sorting through it all can be overwhelming. Generative AI can cut through this data noise.

Generative AI uses large language models, tools trained on massive text-based data sets, to understand natural language and generate clear, conversational responses to queries. For fleets, generative AI can analyze structured data and quickly surface meaningful insights, summaries and suggestions, helping pinpoint the information that matters most.

The idea is this: Instead of manually digging through dashboards, managers can receive personalized summaries or trend alerts, like changes in driver behavior, or an uptick in idling, automatically on a daily or weekly basis.

With contextual, natural-language insights, fleet managers can interact with their data in the way they would a colleague, asking questions like “Who are our safest drivers this week?” or “What assets are due for service soon?” Generative AI would offer relevant answers in seconds.

Generative AI fleet management could offer:

• “Clean speak” AI assistants for managers and drivers with question/response dialogue. 
• Added detail, interpretation and summarizing of information. 
• Natural language commands and queries for topics such as productivity or metrics. 
• Graphic, voice, video and document support.
• Tha ability to provide preferences, goals and past queries for personalized interactions. 

Established use cases for AI fleet management

While truly conversational AI that digs up insights on its own isn’t widely adopted in the fleet management marketplace yet, there are some compelling use cases for AI fleet management already, primarily in video telematics. AI is being used to help spot, catalog and analyze driver behavior to strengthen safety and accountability within fleets.

Dashcams: Unlike standard dashcams, AI-enabled models combine dual-facing cameras with onboard telematics, AI algorithms and edge computing. This “smart video” system automatically detects risky driving behaviors in near-real time, like distracted driving, harsh braking and tailgating. Managers are alerted and can make informed decisions about what action is needed. Verizon’s AI dashcams also offer in-cab alerts to help drivers self-correct in the moment.

Cloud video analysis: Once footage is captured, it’s automatically uploaded to the cloud, where AI tags and classifies videos (e.g. “stop sign violation”) based on severity. Managers can easily search, review and share high-quality clips with a full, multi-perspective view in HD detail. 

These can help with personalized coaching efforts, support driver scorecarding and protect against false claims.

These kind of video- and cloud-based AI fleet solutions can help reduce costs by helping to manage: 

• Accident and false claim costs 
• Insurance premiums
• Vehicle wear and tear
• Medical or compensation payouts
• Fuel efficiency
• Manual safety reporting and documentation

Want to take a deeper dive into innovative AI dashcam technology? See how it can help focus on fleet safety and reduce costs 

What’s next for AI fleet management?

While upcoming generative AI fleet tools will help fleet managers uncover useful video insights, the future points toward even more intelligent and autonomous capabilities.

Agentic AI is a form of AI that doesn’t just generate insights but also takes action on its own. This kind of AI program would run reports based on specified data sources, conduct analysis and automate workflows with independence. It may surface the same kinds of insights as generative AI, but then take the next step and proactively adjust routes, reassign vehicles or schedule maintenance automatically, all with minimal human input.

As this technology evolves, so do the responsibilities that come with it. Oversight for accuracy, transparency and ethical use will all be critical to effective use of AI and maintaining trust with workers and customers.

It’s important that fleet managers understand how a particular insight was generated, the data that informed it and how they can validate it if necessary. This gives everyone confidence in the validity of their information and helps support better, holistic decision-making. The goal isn’t just automation at all costs, but trustworthy, transparent automation that is still accountable to human workers.

AI fleet management is only going to accelerate over time. Fleet managers must be ready to think critically about its benefits and drawbacks and be ready to jump when the time is right.

To explore how Verizon Connect uses AI in our fleet management solutions, book a demo today.

Sources:

¹ How Fleet Managers Are Using Generative AI to Transform Daily Operations 

² EVAI Survey Reveals GPT Opportunities and Challenges for Fleet Management