5 Energy Companies Using AI for Cost-Efficiency

The use of artificial intelligence is increasing as more industries, such as energy companies, adopt the technology that mimics human abilities and provides predictive analytics as part of their daily operations.

AI includes components like machine learning, neural networks and natural language. The energy industry uses it to predict potential failures in equipment, corrosion, or security breaches, improve efficiencies and productivity and increase worker safety.

“AI will incorporate emerging technologies like quantum computing to develop more sophisticated models, which could lead to innovations in grid optimization and breakthroughs in the development of sustainable energy,” says Mahesh Sudhakaran, a chief digital officer at IBM (ticker: IBM).

For instance, IBM’s AI helps the energy sector improve efficiency and reliability such as utilities monitoring their power plants for predictive maintenance and maximum efficiency, he says.

Here’s a look at five energy companies that are harnessing AI to help their bottom line:

— Exxon Mobil Corp. (XOM)


— Schneider Electric (SBGSF)

— BP (BP)

— Royal Dutch Shell (RDS/A)

Exxon Mobil

IBM works with oil companies like Exxon Mobil to explore the use of quantum computing to accelerate the development of more realistic simulations with artificial intelligence, in addition to developing chemistry calculations for more efficient carbon capture.

“Service interruptions cost the energy sector millions of dollars a year and can negatively impact return on equity, customer satisfaction and safety,” Sudhakaran says.

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Companies that are more efficient can save money and time, generating more profits. XOM has a 4% dividend yield.


Companies use AI to detect faults such as cracks in pipelines and machinery by analyzing images. This saves companies money and minimizes downtime when equipment breaks down, says Guido Jouret, chief digital officer of ABB, a Swiss power and automation company.

“An AI pilot project with one of the world’s largest hydroelectric utilities showed a 10% reduction in routine maintenance and a 2% increase in output,” he says. “These measures translate into millions of dollars in cost savings.”

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In the future, AI can help manage distributed energy resources, such as energy storage, demand and generation to ensure reliable green power, Jouret adds.

“Oil companies are also using AI to analyze seismic data to find and optimize the extraction of oil,” he says.

The dividend yield for ABB is 4.3%.

Schneider Electric

Artificial intelligence turns massive volumes of data into information that creates more efficiency and sustainability, says Herve Coureil, chief digital officer at Schneider Electric, an energy automation company.

These systems are more predictive, resulting in equipment operating longer and reduced maintenance costs, he says.

“Maintenance teams can focus less on repairs and instead on sophisticated analytics to improve operations,” Coureil says.

Schneider Electric leverages Microsoft Corp.’s ( MSFT) machine learning capabilities to monitor and configure pumps in the oil and gas field remotely since early detection of a pump failure can avoid weeks of the equipment being out of commission and repair costs of up to $1 million.

“Our customer Tata Power, India’s largest power generator saved almost $300,000 on a single predictive maintenance catch,” he says.

Schneider Electric utilizes AI to improve productivity and have better margins. The stock has a 3.3% dividend yield.


Artificial intelligence is also used by energy companies in the upstream, midstream and downstream sectors to automate manual tasks, find oil faster with machine learning, recover more oil with the connection of more sensors, lower the cost per barrel and reduce risk and ensure compliance.

Amazon.com’s ( AMZN) cloud computing clients include BP, which used the technology for increased performance of its lubricants ERP system with 40% faster response times.

AI enables companies like BP to increase production of oil and petroleum products, resulting in higher margins. BP’s stock generates a dividend yield of 5.5%.

Royal Dutch Shell

Shell, a global energy company, adopted the use of AI several years ago and utilizes machine learning, computer vision, deep learning to virtual assistants and autonomous vehicles to robotics in its operations. AI is used throughout the company from drilling and extraction to safety for its customers and employees at its gas stations such as conducting predictive maintenance for more than hundreds of thousands of critical assets globally.

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Shell implemented AI to drill in wells in the Permian Basin, said Gretchen Watkins, president of Shell Oil Company at CERAWeek, a global energy conference held in Houston last month. The algorithms from machine learning provide information to produce “safe, reliable, low-cost operations and we will continue to advance in that arena,” she says.

More than 95% of Fortune 500 companies use Microsoft’s cloud centric company Azure. That includes Shell, which utilizes AI technologies to increase revenue, reduce costs and improve the safety of operations, such as monitoring data from drill sensors six miles beneath the earth’s surface.

Shell scaled and replicated AI and machine learning applications across its upstream and downstream businesses and improved operational performance. The technology improved the accuracy and consistency of a horizontal well’s directional control to reach the most productive layers of rock containing oil and gas.

Shell’s stock generates a dividend yield of 5.9%.

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5 Energy Companies Using AI for Cost-Efficiency originally appeared on usnews.com

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