How Industrial AI Creates New Business Models

Artificial intelligence is sweeping virtually every sector and discipline, and has especially thrived in industry as a whole. In fact, it has revolutionized how industrial firms monetize their services.

Industrial AI is, as the name suggests, the use of AI to improve key industrial processes. This is particularly prevalent in the energy sector, where AI has cultivated new ways of doing business.

The Growth of “As-a-Service” Operations

One especially interesting form this has taken is “servicization,” which seeks to replace one-time buys with ongoing subscription-esque plans. 

Traditionally, an oilfield operator would simply purchase their pumps, compressors, and rigs and operate them independently. However, they would foot the bill for any maintenance or repairs.

Now, vendors effectively “loan” the equipment for a rolling fee, while using AI analytics to predict maintenance needs and sell nearly guaranteed outcomes. They could use this to charge:

• Per barrel lifted (pumping)
• Per foot drilled (drilling)
• By sheer uptime (compression)

In this model, vendors also assume responsibility for maintenance. That said, they don’t take on the same risks as operators previously did, as they have the data to sidestep downtime.

This shift was already happening before AI’s sudden growth. However, vendors can now provide more reliable (and real-time optimized) equipment than ever, allowing them to embrace low-risk outcome-based contracting.

Selling Datasets

Oil and gas AIs work with, extrapolate, and generate high volumes of data, including:

• Seismic imaging
• Drilling logs
• Well production data
• Environmental monitoring
• Digital twins

Operators can then license this data and sell it to other companies — especially energy startups needing to embrace the industry’s digital revolution. Vendors can also make digital twins of their own equipment and sell these as an additional service to help with long-term maintenance.

This has the potential to make the whole sector much safer. For example, a company could sell a bit-wear model with data from thousands of wells to see how a drill bit performs over time. In a sector filled with risk, fledgling energy firms could rely on this to confidently make decisions.

Decarbonization

Companies can now use AI to track methane leaks, adjust flare stacks, check carbon footprints, and generally optimize CO2 capture. They can sell each of these as individual services — or as several parts of an overall decarbonization package.

AI software developers can offer this functionality, or supermajors in the industry (such as Shell) could license their internal decarbonization products to smaller firms. 

A decarbonization service could take any of the following forms:

• A monthly subscription to access AI-powered data dashboards
• A charge for every ton of CO2 that the company avoids/captures
• Selling low-carbon oil and gas at a higher-than-market rate
• Vendors get a percentage of their clients’ carbon cost savings

Overall, this could transform a regulatory process into a whole new revenue stream. Any oil and gas company that adopts this approach could also enjoy a reputation boost, as they’ll transition from emitter to solutions provider.

Autonomous/Remote Operations

AI allows operators to run drilling operations without a significant human presence on-site. This doesn’t mean AI will replace anyone — the staff will simply work in a centralized control center. Operators will always still need staff to act in an emergency or double-check AI decisions.

With the correct AI, operators will have systems that can adjust their pressure and flow rate at a moment’s notice. They’ll also use predictive maintenance to address minor issues, reserving the actual maintenance crews for more serious matters.

Here are just some of the opportunities this opens up:

• Vendors operating a client’s assets entirely remotely and charging for uptime
• AI-guided rigs that prioritize outcome-based contracts (i.e., per foot drilled)
• Operators charging for AI-driven inspections, such as via autonomous drones
• Vendors providing real-time monitoring and alerts as a monetized service

How Oil & Gas Companies Already Use Industrial AI

Industrial AI isn’t something that might happen or could take the oil and gas sectors by storm. If anything, it already has. Here’s how top firms are already integrating it into their services:

• Shell: Since 2018, Shell has been using C3 AI to carry out predictive maintenance. They also use generative AI and deep learning to optimize seismic surveys.
• ExxonMobil: ExxonMobil’s Guyana operations are among the first to utilize autonomous drilling. It also works with Microsoft’s IoT tools to collect data in the Permian Basin.
• BP: BP has used Palantir’s AI solutions for over a decade — this includes using LLMs to complement human decisions and develop more reliable digital twins.
• ADNOC: ADNOC has successfully generated over $500 million in value from over 30 AI tools, which have helped reduce shutdowns and massively limit CO2 emissions.

The Future of Industrial AI

Many energy companies are embracing industrial AI, though few are transforming this into new services for other enterprises. This could be especially useful for mid-tier companies wanting to lease infrastructure and data to oil and gas startups.