Artificial intelligence (“AI”) is quickly becoming a competitive necessity across the oil/energy sector. Faced with volatile commodity prices, rising operating complexity and tighter emissions scrutiny, energy majors are embedding AI into daily operations to improve execution and protect margins. Supermajors such as BP plc ((BP Quick QuoteBP - Free Report) ), Chevron ((CVX Quick QuoteCVX - Free Report) ), ExxonMobil ((XOM Quick QuoteXOM - Free Report) ) and TotalEnergies ((TTE Quick QuoteTTE - Free Report) ) are now using AI to gain competitive advantages that seemed impossible just 10 years ago.

For long-term investors, AI capability increasingly signals more than innovation. It reflects discipline around cost control, operational consistency and scalability, all of which matter for durable returns in a capital-intensive industry.

Why AI Capability Matters for Long-Term Energy Investors

AI allows energy companies to analyze massive volumes of operational data in real time, turning complexity into actionable insight. This digital efficiency supports faster decisions, fewer disruptions, and better asset utilization, strengthening competitive positioning over full commodity cycles.

Just as importantly, AI tools increasingly support emissions monitoring and predictive maintenance, aligning profitability with sustainability goals. Companies that integrate AI into core workflows may be better equipped to balance efficiency, safety and regulatory pressure over time.

BP’s Aggressive Digital Push

BP stands out for the scale and depth of its AI adoption. Central to its strategy is a long-term partnership with Palantir Technologies ((PLTR Quick QuotePLTR - Free Report) ) that has produced a digital copy — or digital twin — of BP’s global operations, spanning the Gulf of America, the North Sea and Oman’s Khazzan gas fields.

This system integrates data from more than two million sensors, enabling real-time monitoring of assets and faster responses to changing conditions. Under a five-year agreement, the British oil major is expanding the platform by incorporating Palantir’s Artificial Intelligence Platform, which enhances AI-driven recommendations while reducing generative AI risk. BP consistently points to these capabilities as the key drivers of drilling efficiency, asset reliability and emissions monitoring.

Chevron’s Practical AI Applications in Shale and Refining

Chevron is taking a more targeted, execution-focused approach to AI adoption. Through a partnership with Percepto, the Zacks Rank #3 (Hold) company is deploying AI-enabled autonomous drones across shale operations in Texas and Colorado to detect methane leaks, equipment failures and maintenance issues. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

Within months, Chevron reported lower unplanned downtime as problems were identified earlier, improving safety and production reliability. Beyond drones, Chevron is using machine learning models in the Permian Basin to optimize drilling parameters, extend equipment life, and reduce operating costs and emissions. The American energy behemoth is now exploring AI-powered drone inspections at refineries worldwide, signaling that successful field-level applications are being scaled across the broader asset base.

ExxonMobil’s Technology Leadership

Another U.S. energy biggie, ExxonMobil, has emerged as a leader in autonomous drilling. The company says it was the first in the industry to deploy AI-driven, closed-loop drilling automation in deepwater projects, notably offshore Guyana, where AI systems adjust drilling conditions in real time without human intervention.

Onshore, machine learning supports production optimization, asset utilization and downtime reduction in the Permian Basin. ExxonMobil is also extending its AI expertise into carbon capture initiatives and plans to supply low-carbon power solutions to the growing AI data center market in the United States.

TotalEnergies: AI for Efficiency and a Greener Future

TotalEnergies is taking a slightly different, yet equally ambitious, path with AI. The French multinational has teamed up with domestic AI startup Mistral AI to create a joint innovation hub. Their focus is on improving industrial performance, boosting energy efficiency and cutting emissions. TotalEnergies is deploying AI tools to optimize both its upstream (exploration and production) and downstream (refining and marketing) operations, including predictive maintenance and emissions management.

Their AI-powered assistant, developed with Mistral AI, helps guide decision-making for project development, managing industrial sites, and providing energy solutions to customers. TotalEnergies believes that AI can directly help it achieve its goal of decarbonization while maintaining high operational efficiency. Notably, TotalEnergies's AI-driven systems help minimize downtime, optimize energy use and manage the integration of renewable energy alongside traditional assets. The leadership at TotalEnergies emphasizes that AI is now just as critical as any physical asset in delivering its long-term strategy.

How Investors Can Assess AI Readiness Across Energy Majors

For investors, AI readiness is best judged by tangible operational outcomes rather than headline announcements. Indicators include reduced downtime, improved drilling consistency, longer equipment life, and evidence that AI tools are embedded into everyday decision-making.

Companies that treat AI as core infrastructure, rather than a standalone technology experiment, may be better positioned to scale efficiencies across cycles. As BP, Chevron, ExxonMobil and TotalEnergies demonstrate, AI is increasingly tied to execution discipline, emissions management, and long-term operational strength.

In an industry where small efficiency gains can translate into meaningful financial impact, AI adoption is becoming a defining factor in how energy majors compete and compound value over time.