As the auto industry continues to face inflation and supply challenges, managing costs efficiently remains a top priority for fleet managers. In particular, fuel has become a major expense for fleets, with fluctuating fuel prices making it difficult to predict costs. In a recent survey of over 300 fleet professionals by ABI Research and Ridecell, 32% of fleet managers said fuel price increases are impacting their businesses.
As of March 2023, acquiring a new vehicle is also reportedly 6.1% more expensive compared to March 2022. As a result, proactive maintenance is another rising yet crucial expense for keeping fleet vehicles in optimal condition and catching potential issues before they escalate.
Additionally, fleet managers are facing rising insurance premiums and claims-related costs. According to the U.S. Bureau of Labor Statistics, motor vehicle insurance costs increased by 22.8% from January 2021 to March 2023. Rising workforce costs, including driver wages, benefits, and overtime, also make balancing costs with operational efficiency a burdensome task.
Today, more and more fleet managers are turning to digital solutions to figure out where they can cut costs. In particular, artificial intelligence (AI) is helping automate fleet data collection and expense analysis.
Here’s a deeper look at how AI technology can help fleet managers identify patterns in driver behavior, monitor fuel prices, and provide recommendations to reduce costs.
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Improving fleet data analysis
Telematics and IoT technologies are already commonly used to collect real-time data from vehicles and drivers. However, combining this data with AI can provide valuable insights into fleet performance and cost drivers. For example, AI-powered telematics systems can help fleet managers monitor vehicle health, driver behavior, and fuel efficiency.
AI-driven predictive analytics can also be used to identify patterns and trends in fleet data, enabling more proactive cost management strategies. By analyzing historical data and predicting future events, fleet managers can make better maintenance scheduling, resource allocation, and risk management decisions, ultimately reducing costs.
Optimizing fleet operations
According to ABI Research and Ridecell’s survey of over 300 fleet professionals, nearly 95% of fleet managers said their business is being impacted by increasing overhead costs. A lack of streamlined processes can add to the challenges fleet managers face. Without efficient systems for data collection, analysis, and reporting, managers may find themselves spending excessive time and effort on administrative tasks, taking away from their ability to focus on strategic initiatives.
The survey also uncovered that 62% of fleet managers said digitization is their top priority, and 55% listed workflow automation specifically as a top priority.
AI is helping tackle fleet operational expenses in several ways. For example, AI-driven solutions can help identify inefficient driving behaviors and vehicle performance issues that contribute to higher fuel consumption. AI algorithms can also help analyze factors such as weather and road conditions to identify the most efficient routes for drivers. Optimized routing can reduce fuel usage, increase fleet productivity, and ultimately help lower operating costs.
Predictive maintenance tools powered by AI are also on the rise for analyzing vehicle data and identifying potential maintenance needs before they become costly issues. Implementing preventive maintenance strategies based on AI-driven insights can help extend vehicle life, minimize downtime, and reduce maintenance costs. Companies using fleet management technology reported a 17% decrease, on average, in costs.
Automating risk assessment and claims processes
AI can also play a vital role in reducing costs surrounding risk assessment and claims processes. By analyzing historical data and utilizing machine learning algorithms, fleet managers can more accurately predict the likelihood of accidents, breakdowns, and other incidents. This predictive capability allows managers to take proactive measures to prevent accidents and associated costs.
AI technology can streamline the insurance claims process as well, automating tasks such as damage assessment, claims handling, and fraud detection. Faster and more accurate claims processing can reduce administrative costs and improve customer satisfaction, lowering overall insurance-related expenses for fleet managers.
Embracing AI and keeping fleet costs under control
Fleet managers must continuously innovate to remain competitive, and embracing AI technology will be crucial for success and unlocking new opportunities for cost optimization. As AI continues to evolve, its integration with other emerging technologies, such as edge computing, 5G, and computer vision (visual intelligence) technologies will further enhance its cost-cutting capabilities. Combining these technologies can lead to improved data collection and more automated processes, ultimately resulting in greater savings and operational efficiency.
Author: Julio Pernía Aznar, CEO of Bdeo
