The future of the oil and gas industry will be shaped by a range of disruptive themes, with artificial intelligence (AI) being one of the themes that will have a significant impact on oil and gas companies. A detailed analysis of the theme, insights into the leading companies, and their thematic and valuation scorecards are included in GlobalData’s thematic research report,Artificial Intelligence (AI) in Oil and Gas – Thematic Research.  Buy the report here.

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The oil and gas industry is facing many severe challenges, not least the shortage of easily accessible hydrocarbon reserves, forcing companies to explore far and remote reserves that are hard to discover, costly to explore and produce, and risky. Adding to this are the issues regarding sustainability, which can potentially shift demand away from oil and gas towards cleaner sources. Further, huge operational expenses and the asset-heavy nature of the industry make adaptation to newer consumption patterns slow and difficult.  


Although pandemic-related concerns have largely subsided, cost challenges persist. In this scenario, companies must resist conventional expense reduction measures and instead invest in technological transformation. The market has changed, and evolution is necessary. Companies that can become more efficient, more effective, and more aligned with the market’s direction will survive and thrive. 

The oil and gas sector is no exception as companies collect exceptional quantities of data, but a large share of it goes unused. As a result, companies using AI can better harness the power of this data which will further assist in overcoming their challenges and position for long-term success.  

However, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned and ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position.  

According to GlobalData’s thematic research report, Artificial Intelligence (AI) in Oil & Gas, leading adopters of AI include Shell, BP and ExxonMobil.  

Insights from top ranked companies  


Shell has deployed AI across its entire oil and gas supply chain, with over 160 active AI projects. It uses reinforcement learning in its exploration and drilling programme to reduce gas extraction costs. Automated drilling systems trained on Shell’s collected data and data from simulations help the drill operator understand the environment, accelerating results and reducing maintenance and costs. Shell’s Shell. AI Residency Programme gives data scientists and AI engineers experience with several AI projects across the company. 

In the emerging electric vehicle (EV) market, Shell’s RechargePlus programme uses AI to predict the varying demand for EV charging terminals throughout the day so that power can be supplied more efficiently. At its retail stations in Singapore and Thailand, Shell uses cameras with computer vision to identify customers lighting cigarettes near pumps and refuelling vehicles. When such behaviour is detected, forecourt staff are alerted and can close nearby pumps to reduce risk.  


Another European oil major, BP, has partnered with Microsoft since 2017 to implement its Azure cloud solutions, including machine learning (ML) for smarter drilling processes. This partnership allowed BP to move all its data centers to Azure. It accelerated the data analysis and facilitated faster, more effective decisions, which has significantly reduced the drilling time.  

BP partnered with Bluware in 2020 to use deep learning to accelerate digital transformation initiatives. The project will improve subsurface data interpretation by eliminating manual, time-consuming interpretation of seismic data. 

BP has invested in many AI companies, including Grid Edge and Belmont Technologies to boost decision making. Grid Edge is an AI-based energy management platform that helps customers optimise their building’s energy profile. Belmont Technologies’ industrial AI software provides key operational insights and enables process automation and optimisation across all operations. Beyond Limits uses AI to identify the location of O&G reserves. Satelytics Investment is a cloud-based geospatial analytics software company that uses ML to detect leaks and alert users to facility risks by monitoring environmental changes, such as methane emissions. R&B Technology Group produces smart devices and services focusing on building energy management. 

Besides, BP has trialled the AI-driven Spot robot at a refinery. The robot gathered data, detected abnormalities and emissions, and removed workers from hazardous spaces. BP also implemented the Castrol Brain chatbot to answer queries from marine customers, saving time and allowing employees to focus on complex queries. 


ExxonMobil, a prominent adopter of digital technologies in the oil and gas sector, collaborated with IBM’s Data Science and AI Elite Team and seismic experts to use AI to interpret and integrate data from siloed systems into one repository. The repository is hosted on a multi-cloud environment. The availability of the data from any location has enabled faster decision-making across functions. A partnership with Fiserv, a payments and financial services company, enables customers to pay at gas stations with Alexa technology and Echo Auto. The payments were processed with Amazon Pay. Exxon has also partnered with MIT’s AI lab to develop AI-powered, self-learning, submersible ocean exploration robots. 

To further understand the key themes and technologies disrupting the oil and gas industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Oil & Gas.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Thematic Scorecard ranks companies within a sector based on their overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of their future earnings and relative position within key strategic areas.