Artificial intelligence (“AI”) is becoming an important tool for oil/energycompanies. These businesses operate large and complex assets, including drilling sites, pipelines and refineries. AI can help them study huge amounts of data, spot equipment problems earlier and make faster operating decisions.

For investors, simply using AI is no longer enough. What matters is whether companies can use the technology to lower costs, reduce downtime and improve productivity. Major energy operators, such as BP plc (BP Quick QuoteBP - Free Report) , Chevron (CVX Quick QuoteCVX - Free Report) , ExxonMobil Holdings (XOM Quick QuoteXOM - Free Report) and TotalEnergies SE (TTE Quick QuoteTTE - Free Report) , are increasingly using AI for their normal operations.

Why AI Matters for Energy Companies

Oil and gas operations generate enormous amounts of information every day. Data comes from wells, drilling equipment, pipelines, refineries and other facilities. Going through all this information manually can be difficult and time-consuming.

AI can analyze the data quickly and identify patterns that people may otherwise miss. For example, it can warn operators that equipment may fail, help determine better drilling methods or show where production can be improved.

These benefits can mean fewer interruptions, lower repair costs and better use of expensive assets. For investors, that is where AI becomes important: the technology can help energy companies operate more efficiently even when oil and gas prices are volatile.

BP Expands AI Across Its Operations

BP has been investing heavily in digital technology and AI. Its long-running partnership with Palantir Technologies (PLTR) has helped the company bring information from different operations onto common digital platforms. BP uses a digital model of its global operations, supported by data from millions of sensors, to monitor assets in real time and respond more quickly to operating issues.

The focus has increasingly shifted toward using these tools in everyday work. AI can help BP identify production problems earlier, improve planning and reduce the amount of time employees spend reviewing large amounts of technical information.

For investors, the important point is not the technology itself. The bigger benefit would come from BP using AI across more assets to improve reliability, control costs and keep production running efficiently.

Chevron Uses AI to Solve Practical Problems

Chevron has taken a practical approach to AI. One example is the use of automated drones to inspect oil and gas facilities. These drones can help detect methane leaks, equipment problems and other issues without requiring workers to inspect every location manually.

Chevron is also using machine learning to improve drilling and production, particularly in the Permian Basin. These tools can study past operating data and help employees decide how wells should be drilled or managed.

The benefit is fairly straightforward. If Chevron can identify problems sooner, drill more efficiently and keep equipment operating longer, it can reduce costs and avoid lost production. That makes AI especially useful in large shale operations where even small improvements can add up across many wells.

ExxonMobil Brings More Automation Into Drilling

ExxonMobil has been using AI to automate parts of the drilling process. Its systems can analyze drilling conditions and make adjustments while a well is being drilled. The Zacks Rank #3 (Hold) company has used this type of technology in offshore Guyana and has also applied machine learning to its Permian operations.

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Since drilling is costly, reducing delays and avoiding errors can have a meaningful impact on expenses. Greater automation can also make drilling more consistent and reduce the need for repeated manual adjustments.

ExxonMobil is also looking at AI from another angle. Rapid growth in AI and data centers is increasing electricity demand, creating potential opportunities for energy producers that can provide reliable power. This gives ExxonMobil exposure both as a user of AI and potentially as an energy supplier to the expanding AI economy.

TotalEnergies Uses AI Across a Broader Energy Business

TotalEnergies is working with French technology company Mistral AI to expand the use of artificial intelligence across its operations. The partnership is aimed at improving industrial performance, energy efficiency and decision-making.

AI can help TotalEnergies study exploration data, monitor refineries and identify maintenance needs before equipment breaks down. It can also help employees work through large amounts of technical information more quickly.

TotalEnergies has an especially broad range of businesses, spanning oil, natural gas, electricity and renewable energy. That gives the company several areas where AI could improve efficiency. The value for investors will depend on whether these tools lead to lower operating costs, improve asset performance and lead to more reliable execution.

What Should Investors Look For?

Energy companies regularly announce partnerships involving AI, but investors should focus on results rather than announcements.

Useful signs include less downtime, faster drilling, lower operating costs, better production forecasts and longer equipment life. Another important question is whether AI is being used across many assets or remains limited to small pilot projects.

BP, Chevron, ExxonMobil and TotalEnergies are all using AI, but in somewhat different ways. BP is applying digital tools across its global operations. Chevron is focusing heavily on practical applications in drilling, inspections and shale production. ExxonMobil is pushing further into drilling automation and large-scale data analysis, while TotalEnergies is using AI across its oil, gas, refining and broader energy businesses.

AI alone will not determine which energy stock performs best. Oil and gas prices, project execution and capital spending will remain much more important. However, companies that use AI to cut costs, avoid disruptions and get more from their existing assets could gain an operational advantage over time.