Practical Use Cases for AI in Fleet Management
Using AI to turbocharge your fleet management services.
- The customer relies on historical information for making decisions.
- There is a fleet manager that cannot keep up with the pace of change.
- Real-time decision-making is needed for keeping costs down.
- The company is growing rapidly and needs help scaling up.
Our Advice
Critical Insight
- In contrast to using older methods such as business intelligence (BI), which relies on your knowledge of what questions to ask, artificial intelligence (AI) relies on data to determine the most important factors influencing outcomes and to suggest changes.
- The market is becoming more competitive, and customers are becoming more demanding. Advanced technology solutions with AI/ML have become normal expectations from customers, suppliers, and partners, and with that comes transparency across every step of the journey.
Impact and Result
- Predict any potential problems or roadblocks.
- Enable higher levels of collaboration and delivery execution.
- See greater efficiency and customer satisfaction.
Practical Use Cases for AI in Fleet Management
Use AI to turbocharge your fleet management services.
Analyst Perspective
Achieve powerful decision generation through real-time AI in fleet management.
Fleet managers can benefit from artificial intelligence (AI) because it streamlines data management, helps to prevent problems, and enables collaborative monitoring. AI can also be used for mentoring and coaching programs and real-time training.
Data is being generated at an exponential rate due to technological advancements, making it nearly impossible for humans to perceive and analyze all the data in a timely manner. Fleet managers will increasingly need to use AI if they want to keep up with the exponential growth in demand for scalable transportation solutions and infrastructures.
Machine learning (ML) analyses and reports on the large data sets produced by your telematics system and its two primary capabilities are data-driven pattern recognition and recommendations. However, your telematics system will soon be able to offer prescriptive instructions.
In contrast to using older methods such as business intelligence (BI), which relies on your knowledge of what questions to ask, AI relies on data to determine the most important factors that are influencing outcomes and to suggest changes that will deliver results.
Kevin Tucker
Principal Research and Advisory Director, Industry
Manufacturing, Supply Chain, Logistics, and Transportation
Info-Tech Research Group
Executive Summary
| Your Challenge | Common Obstacles | Info-Tech's Approach |
| Your organization needs help managing the escalating costs of fleet management. Many of the day-to-day activities required for effective fleet management are very costly to track and perform. The biggest challenge is how to track expenses, theft, ESG (environmental, social, and governance) compliance, route adjustments, and driver behaviors that may impact the ongoing costs of the business.
The market is becoming more competitive, and customers are becoming more demanding. Advanced technology solutions are now expected from customers, suppliers, and partners. Along with that is the transparency required across every step of the product journey. |
Figuring out where to start using AI in the business can be difficult. Many organizations have a wide array of legacy equipment and unsupported programs in use.
A business case for adopting AI solutions needs to be developed. Many businesses feel they are doing a good job with outdated tools, and they do not want to take on more technical debt to resolve the daily operational and resource availability problems. Improved workforce skills and change management are needed to overcome the skills gaps and provide effective budgeting for the investment. |
We recommend identifying some specific use cases that are most applicable to the needs of your organization and will offer the best short-term benefits.
Use this report to help you determine where the value proposition can help elevate your business case for change. Create collaborative partnerships with industry peers, technology companies, and experts who can offer collaboration and guidance. We work closely with our customers to provide both strategic decision-making and advisory services. |
Info-Tech Insight
AI is revolutionizing the way that companies operate. Companies that are experiencing exponential growth can leverage AI in fleet management use cases and help from Info-Tech to provide practical ways to use technology for streamlining their fleet business.
Many organizations are accelerating their focus on AI
A recent study showed where organizations are directing their focus on AI as they move toward real-time data-driven decision-making.
Source: TechTarget, 2023
AI has already been powering some aspects of fleet management. However, AI is now becoming much more important as companies struggle with escalating costs and difficulties hiring and retaining staff.
Decision-making can be powered by AI
AI can also fix a lot of other problems once it's set up. However, many organizations are facing challenges with current ecosystems.
An organization's ability to swiftly replace legacy systems or implement new AI solutions is hindered by integration issues. These issues also impede obtaining the necessary budget.
Businesses face difficulty implementing AI.
- 27% of businesses have difficulty implementing AI programs and replacing outdated solutions.
Legacy systems are challenging to replace.
- Based on customer interactions, Info-Tech estimates that 40% of businesses encounter difficulties when replacing and integrating legacy systems.
The fleet management market is poised for exponential growth
No longer a well-kept secret, AI drives projected growth for fleet management.
Current Market
$25b
2022
Older fleet management systems have some traditional embedded AI, but nothing overly sophisticated.
Market Projection
$52b
2027
Generative AI (Gen AI) has truly captured our imagination. Companies are now scrambling to develop practical solutions to drive the next wave of growth.
Source: Purview, 2023
AI powers fleet management technology boom
01 Vehicle Purchase or Loan
Ratings and negotiations for new or shared vehicles.
02 Product Load & Delivery
Load Optimization, scheduling, and delivery management.
03 Vehicle & Driver Monitoring
Onboard visual monitoring and telematics for driving efficiency
04 Fleet Expense Management
Ongoing location finders as well as vehicle and human expense management
05 Vehicle Maintenance
Onboard monitoring for predictive maintenance services.
06 Selling and Scrapping
Pricing negotiation for selling and scrapping vehicles
AI fleet management is driven by technology
Cloud Computing
Cloud computing enables the computing power to manage trillions of data points for your historical, current, and forecast data.
Telematics
Collects real-time data on vehicle/human health from sensors
Machine Learning
Captures data and feeds it back and forth between telematics and analytics
Natural Language Processing (NLP)
Captures operator voice requests, and translation and return vocal information
Mobile
Provides access to information anytime and anywhere it is needed
Internet of Things (IoT)
Refers to the protocol and technology for all the integrations
Big Data Analytics
Includes the AI models that enable real-time decision-making
Computer Vision
Provides human-machine safety and evidence-based accident defense
Blockchain
Provides secure and transparent business to business (B2B) supplier/ partner transactions
Human-Machine Interface
Enables humans and robots to share the same interfaces
Edge Computing
Provides reliable connectivity from any location across the ecosystem
Fleet management system capabilities
Licensing & User Management
It is vital that there is a thorough understanding of the different types of users that will need access to the solution and how the licensing model is applied for each individual user.
Integration & Security
Integrations that are within the core functions of the system and reach out to other enterprise systems should be coupled with physical security and cybersecurity to keep out all bad actors.
AI is everywhere but not always visible
AI is becoming a key contributor to the fleet management solution market, so you need to understand how to deliver impact.
AI Impact
1 Be Intentional
Be very clear about the important factors (e.g. policy, transparency, ethics, accountability, safety, accuracy requirements) for the adoption of all AI solutions.
2 Identify Embedded AI
The product has AI embedded into it, and you may not be able to directly interact, configure, or influence it.
3 Unmask Invisible AI
The product has AI embedded into it, but you cannot see or touch any aspect of the AI capabilities.
4 Fix Hallucinations
Incorrect or misleading information generation and related deception, such as AI pretending to be human, must be tightly managed.
5 Enforce Responsible AI
Learn how to build, buy, and deploy AI solutions that are trusted both internally and externally, and educate the business on responsible use of AI.
The best use of AI involves having an intentional approach to its use across the organization.
About Info-Tech
Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.
We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.
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Unlock Sample ResearchContributors
- Brian Buddemeyer, Vice President IT, Spang & Company
- Jay Stanley, Vice President IT, Heartland Food Products Group
- Steven Schmidt, Managing Partner, Manufacturing and Transportation, Info-Tech Research Group