Artificial intelligence (AI) tools, such as ChatGPT and Google’s new AI product Bard, generate excitement and present new opportunities for organizations in various industries, including transportation fleets. These advanced AI-driven resources, including natural language processing capabilities, can enhance:
- Equipment asset management.
- Maintenance and repair (M&R) operation.
- Overall fleet optimization.
Like many other leading-edge technology resources today, these advanced AI tools possess incredible promise. However, it is crucial for executives to carefully evaluate the advantages and disadvantages of relying on these tools in day-to-day fleet operations.
What are AI tools like ChatGPT?
AI tools, like ChatGPT, have gained significant attention since their release, with the transportation and supply chain industries particularly intrigued by their capabilities. Despite the Chat Generative Pre-Trained Transformer (ChatGPT) still being in its infancy stages, the technology, powered by AI and natural language interaction, offers rapid responses and detailed answers, promising increased organizational visibility, streamlined communication, and optimized operations.
Within the corporate transportation fleet context, AI and ChatGPT can significantly impact three key areas in running a corporate transportation fleet: – asset management, equipment finance, and M&R planning and operations.
As an example, when you ask ChatGPT why asset management is important for equipment finance it offers the following excerpts:
“Asset management helps to maximize the value of equipment over its lifespan by ensuring that it is properly maintained and used efficiently. This can lead to reduced downtime, increased productivity, and extended equipment life, ultimately increasing the equipment's overall value. Asset management enables finance companies to effectively plan for equipment replacement or upgrades, ensuring that they can provide clients with the most up-to-date and efficient equipment possible. This can also help finance companies to manage cash flow and budget more effectively.”
Limitations of Using AI
While ChatGPT provides a high-level overview of asset management, it may offer inaccurate or inconsistent information. For instance, traditional finance companies and banks do not play a role in equipment replacement or upgrades.
If you ask ChatGPT to build an asset management plan for a Class-8 heavy-duty truck fleet, it will provide baseline topics to consider, such as equipment inventory, preventative maintenance, telematics and IoT solutions, driver training and safety programs, replacement and upgrade planning, budget and cash flow management, and reporting.
Nevertheless, it’s essential to recognize that AI tools like ChatGPT are not designed to answer financial/mathematical questions, but they will defer to the pros and cons of a business transaction like buying or leasing. These tools rely on web references and can provide incorrect answers without the proper knowledge and expertise.
Therefore, it is crucial to understand that any inaccuracies an AI tool produces could result in financial loss, legal implications, or defamation for organizations.
This also includes defining the true source of who actually produces any material developed entirely or in part by an AI tool such as ChatGPT. While regulations and guidelines for AI tool responsibility are yet to be established, it is widely speculated that they may emerge in the future (1).
Where ChatGPT Does a Disservice for Fleets
ChatGPT also falls short when it comes to developing a customized fleet strategy. In fact, aside from the general considerations, ChatGPT does not analyze actual vehicle operating and utilization data, which is essential for effective asset management planning.
Relying solely on a standardized approach without incorporating real-time vehicle operating data can be problematic.
However, customization based on scrutinizing actual truck operating data allows fleets to create tailored fleet modernization plans that provide optimum flexibility and agility within their financial and operational models. While ChatGPT cannot generate such detailed plans, asset management companies are leveraging AI-driven analytics and fleet analysis to closely monitor key fleet metrics that include:
- Lease versus purchase analysis.
- Sales tax analysis.
- Unbundled versus full-service lease analysis.
- Comparative cost analysis to determine the optimal time to upgrade equipment, etc.
- Per unit profit and loss.
- Predictive life cycle modeling.
Where AI Is Assisting Operational Functions
Aside from asset management and procurement, AI tools, beyond ChatGPT, are significantly impacting operational functions across various industries.
Several recent studies have shown the significant benefits of AI-powered technologies, which can reduce errors in supply chain management by 20% to 50%, according to McKinsey & Company.
Furthermore, the Boston Consulting Group offers a report that shows how AI may help organizations achieve $1.5 trillion in additional value from increased productivity and reduced downtime in the global industrial sector by 2030.
For M&R operations within the manufacturing sector, a separate McKinsey report found that AI-enhanced predictive maintenance of industrial equipment will generate a 10% reduction in annual maintenance costs, up to a 20% downtime reduction, and 25% reduction in inspection costs.
Optimum Asset Management Strategies
Total Cost of Ownership (TCO) analytic tools built by companies that provide life cycle cost management with billions of miles of data and understand the full scope of TCO are continuously monitoring economic factors, used truck values, depreciation, emissions, performance data, and equipment costs to determine the optimum asset management strategy.
Concerning M&R, they also identify potential problems and redeploy corrective actions to prevent truck breakdowns and mechanical failures.
This insight from asset management partners is enabling corporate transportation fleets to move from a traditional, reactive approach in maintenance to a predictive or even preventive approach.
Customized TCO Analytic Tools
Again, tools like ChatGPT can provide high-level input and guidance, but may not offer specific insight to a particular fleet.
This is important because customized TCO analytic tools that leverage predictive modeling allow organizations with transportation fleets to create future business insights with significant accuracy.
With the help of sophisticated data analytic tools and modeling, these firms can use past and current operating data to reliably forecast budget trends in milliseconds, days, or years into the future.
Collaboration between organizations and asset management partners becomes crucial as more AI-powered tools emerge for transportation fleets.
Asset management partners can help fleets identify the most suitable AI tools for their specific challenges and ensure effective integration into fleet operations.