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Leveraging the benefits and understanding the limitations of using AI resources in oil & gas fleet operations, including ChatGPT

Artificial intelligence (AI) tools, such as ChatGPT and Google’s new AI product Bard, are generating excitement and presenting new opportunities for organisations in various industries, including oil and gas organisations with transportation fleets. These advanced AI-driven resources, including natural language processing capabilities, offer the potential to enhance equipment asset management, maintenance and repair (M&R) operations and overall fleet optimisation.

Like many other leading-edge technology resources today, these advanced AI tools possess incredible promise for oil and gas companies. However, it is crucial for their executives to carefully evaluate the advantages and disadvantages of relying on these tools in day-to-day fleet operations.

AI is already helping oil and gas companies assess the value of specific reservoirs, customise drilling and completion plans according to the geology of the area and assess risks of each individual well. Now, these companies are also looking at how AI could benefit their transportation 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 in its infancy stages, the technology, powered by AI and natural language interaction, offers rapid responses and detailed answers, promising increased organisational visibility, streamlined communication and optimised 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 maximise 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.”

While ChatGPT provides a high-level overview of asset management, it may offer some 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 an oil and gas 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 important to recognise that AI tools like ChatGPT are not designed to answer financial/mathematical questions, but it will defer to 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 produced by an AI tool could result in financial loss, legal implications, or defamation for organisations. 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.

Where ChatGPT Does a Disservice for Fleets

ChatGPT also falls short when it comes to developing a customised fleet strategy. In fact, aside from the general considerations, ChatGPT does not analyse actual vehicle operating and utilisation data, which is essential for effective asset management planning. Relying solely on a standardised approach without incorporating real-time vehicle operating data can be problematic. However, customisation based on scrutinising 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 vs Full-Service Lease Analysis
  • Comparative Cost Analysis to determine the optimal time to upgrade equipment, etc
  • Per unit P&L
  • Predictive Life Cycle Modeling

Where AI is Assisting Operational Functions

Aside from asset management and procurement, AI tools, beyond ChatGPT, are making a significant impact on operational functions for oil and gas company executives.

Several recent studies have shown the significant benefits of AI-powered technologies, in which they can reduce errors in supply chain management by 20 per cent to 50 per cent, according to McKinsey & Company.

Furthermore, the Boston Consulting Group (BCG) offers a report that shows how AI may help organisations achieve 1.5 trillion US dollars 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 per cent reduction in annual maintenance costs, up to a 20 per cent downtime reduction and 25 per cen reduction in inspection costs.

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. With regard to 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 oil and gas fleets to move from a traditional, reactive approach in maintenance to a predictive or even preventive approach. 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 customised TCO analytic tools that leverage predictive modelling allow oil and gas fleets to create future business insights with a significant degree of accuracy. With the help of sophisticated data analytic tools and modelling, these firms can use past and current operating data to reliably forecast budget trends in milliseconds, days, or years into the future. As more AI-powered tools emerge for transportation fleets, collaboration between organisations and asset management partners becomes crucial. Asset management partners can help fleets identify the most suitable AI tools for their specific challenges and ensure their effective integration into fleet operations.

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